Factors Affecting Surgical Waiting Time in Cancer Patients at Referral Hospitals of West Java Province
Abstract
A challenge for hospitals in facing the high number of patient visits is to provide quality services. One of the vital services in dealing with patients, especially those who will have cancer surgery considering the high rate of mortality cancer, is an improvement in waiting time (WT). Waiting time for elective surgery is one indicator of service quality with a standard of ≤2 days. This research aimed to determine the average WT for surgery, influencing factors, and optimal queuing models. The method used was quantitative and qualitative methods applied to 207 samples with consecutive sampling at West Java Provincial Al-Ihsan Regional General Hospital Bandung from October to December 2016. The analysis used partial least squares (PLS). The results of the study showed that the average WT for surgery was 32 days. Factors that influence WT were inpatient rooms, number of medical personnel, condition of patients, and health insurance. The optimal queue model to reduce surgical waiting time are adding inpatient beds, oncologist doctor, and creating an online system for registration and confirmation of inpatient rooms and operating.
FAKTOR YANG MEMENGARUHI WAKTU TUNGGU OPERASI PASIEN KANKER DI RUMAH SAKIT RUJUKAN JAWA BARAT
Tantangan bagi rumah sakit dalam menghadapi jumlah kunjungan pasien yang tinggi adalah mampu memberikan pelayanan berkualitas. Salah satu pelayanan signifikan bagi pasien kanker yang akan menjalani operasi adalah perbaikan waktu tunggu karena mortalitas pasien kanker yang tinggi. Waktu tunggu operasi elektif merupakan salah satu indikator mutu pelayanan dengan standar ≤2 hari. Penelitian bertujuan mengetahui waktu tunggu operasi rerata, faktor yang memengaruhi, dan model antrean yang optimal. Metode yang digunakan adalah kuantitatif dan kualitatif yang diterapkan pada 207 sampel secara consecutive sampling di RSUD Al-Ihsan Provinsi Jawa Barat Bandung dari Oktober hingga Desember 2016. Analisis menggunakan partial least squares (PLS). Hasil penelitian menunjukkan bahwa waktu tunggu operasi rerata adalah 32 hari. Faktor yang berpengaruh terhadap waktu tunggu operasi adalah ruang rawat inap, jumlah tenaga medis, kondisi pasien, dan jaminan kesehatan. Model antrean yang optimal untuk menurunkan waktu tunggu operasi adalah penambahan tempat tidur rawat inap, penambahan dokter spesialis bedah onkologi, serta pembuatan sistem daring untuk pendaftaran dan konfirmasi kesiapan ruang rawat inap dan ruang operasi.
Keywords
Full Text:
PDFReferences
Susanti Y, Azis Y, Kusnadi D. Pengaruh appointment registration system terhadap waktu tunggu dan kepuasan pasien. GMHC. 2015;3(1):40–7.
Pusat Data dan Informasi Kementerian Kesehatan Republik Indonesia. Situasi penyakit kanker [Internet]. Jakarta: Kementerian Kesehatan Republik Indonesia; 2015 [cited 2019 November 15]. Available from: https://pusdatin.kemkes.go.id/resources/download/pusdatin/infodatin/infodatin-kanker.pdf.
Ferlay J, Ervik M, Lam F, Colombet M, Mery L, Piñeros M, et al. Global Cancer Observatory: cancer today: population fact sheets [Internet]. Lyon, France: International Agency for Research on Cancer; 2018 [cited 2019 November 16]. Available from: https://gco.iarc.fr/today/data/factsheets/populations/900-world-fact-sheets.pdf.
Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394–424.
Badan Penelitian dan Pengembangan Kesehatan, Kementerian Kesehatan Republik Indonesia. Riset kesehatan dasar (Riskesdas) 2013. Jakarta: Kementerian Kesehatan Republik Indonesia; 2013.
Keputusan Menteri Kesehatan Republik Indonesia Nomor 129/Menkes/SK/II/2008 tentang Standar Pelayanan Minimal Rumah Sakit.
Fitri AN. Analisis waktu tunggu operasi elektif pasien rawat inap di Instalasi Bedah Sentral Rumah Sakit Kanker Dharmais tahun 2014 [undergraduate thesis]. Depok: Universitas Indonesia; 2014 [cited 2019 November 16]. Available from: http://lib.ui.ac.id/naskahringkas/2016-05/S55565-Anasatia%20Nuansa%20Fitri.
Humas RSUP Dr. Hasan Sadikin. Kanker bukan di luar kemampuan kita [Internet]. Bandung: RSUP Dr. Hasan Sadikin; 2015 [cited 2019 November 17]. Available from: http://web.rshs.or.id/kanker-bukan-diluar-kemampuan-kita.
Nilssen Y, Brustugan OT, Eriksen MT, Gulbrandsen J, Haug ES, Naume B, et al. Decreasing waiting time for treatment before and during implementation of cancer patient pathways in Norway. Cancer Epidemiol. 2019;61:59–69.
Wright JG, Menaker RJ, Canadian Paediatric Surgical Wait Times Study Group. Waiting for children’s surgery in Canada: the Canadian Paediatric Surgical Wait Times project. CMAJ. 2011;183(9):E559–64.
Ferdinand A. Structural equation modeling dalam penelitian manajemen: aplikasi model-model rumit dalam penelitian untuk skripsi, tesis dan disertasi doktor. 5th Edition. Semarang: Badan Penerbit Universitas Diponegoro: 2014.
Sholiha EUN, Salamah M. Structural equation modeling-partial least square untuk pemodelan derajat kesehatan kabupaten/kota di Jawa Timur (studi kasus data indeks pembangunan kesehatan masyarakat Jawa Timur 2013). J Sains Seni ITS. 2015;4(2):169–74.
Luque-Fernandez MA, Redondo-Sanchez D, Lee SF, Rodríguez-Barranco M, Carmona-García MC, Marcos-Gragera R, et al. Multimorbidity by patient and tumor factors and time-to-surgery among colorectal cancer patients in Spains: a population-based study. Clin Epidemiol. 2020;12:31–40.
Sangkot HS. Mortalitas dan morbiditas pada pasien elektif dalam daftar tunggu operasi bedah pintas koroner di Unit Pelayanan Fungsional (UPF) Bedah Jantung dan Intermediate Bedah Dewasa RS Jantung dan Pembuluh Darah Harapan Kita tahun 2010 [thesis]. Depok: Universitas Indonesia; 2010 [cited 2019 November 17]. Available from: http://lib.ui.ac.id/file?file=digital/20313277-T%2031717-Mortalitas%20dan-full%20etxt.pdf.
McKevitt E, Dingee C, Warburton R, Pao JS, Brown CJ, Wilson C, et al. Patient navigation reduces time to care for patients with breast symptoms and abnormal screening mammograms. Am J Surg. 2018;215(5):805–11.
Mariella M, Kimbrough CW, McMaster KM, Ajkay N. Longer time intervals from diagnosis to surgical treatment in breast cancer: associated factors and survival impact. Am Surg. 2018;84(1):63–70.
Mariotti G, Siciliani L, Rebba V, Fellini R, Gentilini M, Benea G, et al. Waiting time prioritisation for specialist services in Italy: the homogeneous waiting time groups approach. Health Policy. 2014;117(1):54–63.
Blackmore KM, Weerasinghe A, Holloway CMB, Majpruz V, Mirea L, O'Malley FP, et al. Comparison of wait times across the breast cancer treatment pathway among screened women undergoing organized breast assessment versus usual care. Can J Public Health. 2019;110(5):595–605.
Palvannan RK, Teow KL. Queueing for healthcare. J Med Sys. 2012;36(2):541–47.
Afrane S, Appah A. Queuing theory and the management of waiting-time in hospital: the case of Anglo Gold Ashanti Hospital in Ghana. Int J Acad Res Bus Soc Sci. 2014;4(2):34–44.
Baliski C, McGahan CE, Liberto CM, Broughton S, Ellard S, Taylor M, et al. Influence of nurse navigation on wait times for breast cancer care in a Canadian regional cancer center. Am J Surg. 2014;207(5):686–92; discussion 691–2.
Lee S, Gross SE, Pfaff H, Dresen A. Differences in perceived waiting time by health insurance type in the inpatient sector: an analysis of patients with breast cancer in Germany. Inquiry. 2019;56:46958019875897.
Halpern MT, Schrag D. Effect of state-level medicaid policies and patient characteristics on time to breast cancer surgery among medicaid beneficiaries. Breast Cancer Res Treat. 2016;158(3):573–81.
Mashuri A. Analisis faktor-faktor yang berhubungan dengan waktu tunggu persiapan operasi cito di Instalasi Gawat Darurat Rumah Sakit Karya Medika I Kabupaten Bekasi tahun 2011 [thesis]. Depok: Universitas Indonesia; 2012 [cited 2019 November 18]. Available from: http://lib.ui.ac.id/file?file=digital/20298035-T30149-Aman%20Mashuri.pdf.
Mervin MC, Jackson S. How can we improve waiting time for elective surgery in Australian public hospital. Discussion Paper No. 387 [Internet]. St Lucia, Brisbane: The University of Queensland; 2009 [cited 2019 November 20]. Available from: https://espace.library.uq.edu.au/view/UQ:176138/DP387March2009.pdf.
Askar M. Analisis penyebab keterlambatan dimulainya operasi elektif di Instalasi Kamar Bedah Rumah Sakit Otorita Batam [thesis]. Depok: Universitas Indonesia; 2011 [cited 2019 November 21]. Available from: http://lib.ui.ac.id/file?file=digital/20308042-T%2031668-Analisis%20penyebab-full%20text.pdf.
DOI: https://doi.org/10.29313/gmhc.v8i2.6201
pISSN 2301-9123 | eISSN 2460-5441
Visitor since 19 October 2016:
Global Medical and Health Communication is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.