Figure 2 shows a quantitative summary of the selected corpus, answering RQ1. The 48 selected articles were written by 211 authors. Only 22 (10%) of them participated in two or more studies, never in the same journal. Dispersion of authors and lack of a specific vehicle that concentrates studies is common in research topics about which knowledge is still incipient. Only three studies were authored by multinational research teams: Belgium and the United Kingdom in Cardoen et al. [34], Germany, Switzerland and the Netherlands in Tibesku et al. [35], the USA and Israel in Yoon et al. [22]. A high concentration of authors (82.94%, n = 175, Fig. 2c) and articles (72.92%, n = 35, Fig. 2a) on STR come from the USA, which is not surprising given that it is the country that most spends in healthcare [36], justifying the interest in waste reduction initiatives. Most authors are associated with the Healthcare knowledge area (84.83%, n = 179), followed by Engineering (8.53%, n = 18). Articles authored by healthcare researchers mostly neglect traditional concerns from the Operations Management field, such as improvement standardization actions, and control and monitoring of improvements already implemented.
Journals targeted by authors also reflect their main expertise area: 94.29% of the articles were published in healthcare journals. Authors tend to cooperate with others from the same area producing STR propositions that are often poor as managerial improvement reports. STR studies published in Operations Management journals (e.g. IIE Transactions on Healthcare Systems Engineering, European Journal of Operational Research and Production Planning & Control) usually team authors with different backgrounds (e.g. Engineering, Management, Design) and are methodologically better structured. The Journal of Arthroplasty published the largest number of articles in our corpus (n = 4), although focusing on the use of a patient-customized ST to perform a single procedure (Total Knee Arthroplasty) targeting at trays with fewer instruments (e.g. [37]) that would lead to reduced operating times (e.g. [35]).
The corpus of articles on STR covered 14 surgical specialties and 116 procedures. Most procedures analyzed belonged to the Ophthalmology specialty (40.17%, Fig. 2d), which is volume intensive (i.e. short procedures) and characterized by STs with large number of instruments. Studies that did not mention the specialty analyzed were classified as General Surgery, which appears as the second most investigated (17.09%, n = 20), followed by Orthopedics (11.97%, n = 14).
Figure 2b shows the evolution in the number of articles on STR per year, with around 50% published in the past 5 years. The first study reporting the benefits of STR was published in 1998 in the Obstetrics and Gynecology Journal (JCR = 4.965). The second study, following a gap of more than 10 years, was published in 2007 in the Journal of the American Medical Association (JCR = 10.668). From 2012 on, the subject of STR became increasingly present in the literature.
We now present a thematic analysis of our corpus. We classified STR studies according to their main approach, as follows (Table 2): (i) expert analysis (EA), (ii) lean practices (LP), and (iii) mathematical programming (MP). EA approaches are predominant, accounting for 70.83% (n = 34) of the articles, all of them published in healthcare journals. Most EA approaches were proposed by authors from the healthcare field, with broad knowledge of the surgical specialties addressed. LP approaches are the second more frequent (18.75%, n = 9), with articles mostly published in healthcare journals [n = 8; the exception is Fogliatto et al. [6] published in Production Planning & Control]. MP approaches are the least frequent (10.41%, n = 5), with authors presenting greater background diversity (Engineering, Computing and Healthcare). Most studies targeted a single surgical specialty, and reported rationalizations derived from surgical team meetings and discussions using simple techniques such as consensus groups and checklists, often supported by the analysis of historical data.
We address RQ2 through Table 3, that summarizes STR approaches and the percentage of instrument reduction attained. Most studies (n = 20) report reductions greater than 50%, 9 report reductions between 26% and 50% and in 7, reductions below 25%. No study failed at obtaining improvements in the tray rationalization process, although some did not report quantitative indicators. Classification of techniques was primarily based on authors’ declarations. For example, techniques usually associated with Lean Production were only classified under the LP approach if the study was framed in a lean context. Otherwise, they were classified as EA. In the MP category, studies presented some mathematical formulation of the STR problem.
Tibesku et al. [35] and Stockert and Langerman [38] were the most cited articles from the EA category (based on Scopus citations). Tibesku et al. [35] analyzed cost benefits of implementing Patient Specific Instrumentation (PSI) to perform Total Knee Arthroscopy. To define PSI, authors used interviews (ITV) with surgeons; cost benefits were assessed through ABC costing. PSI reduced the number of STs in 66.67%, leading to smaller sterilization, maintenance, and storage costs. Other articles that used PSI alone or in combination with other techniques were mostly focused on cost reduction, although reporting secondary benefits such as reductions in ST weight [39], OR setup time [40], total time to perform the operation [41], and OR infection rates [37], and improvement in mechanical alignment [42, 43]. Hsu et al. [44] and McLawhorn et al. [45] also reported significant cost reductions in Total Knee Arthroscopy derived from using Template-directed instrumentation (TDI) and a combination of TDI and decision trees (DT). In opposition to PSI which uses disposable items, TDI uses conventional reusable instruments combined with PSI instrument reduction principles.
Table 2
– Classification of STR studies according to main approach
| | Clusters identified |
Journal title | Number of articles | Expert Analysis | Lean Practices | Mathematical programming |
The Journal of Arthroplasty | 4 | [37], [40], [41], [45] | - | - |
Journal of Pediatric Surgery | 3 | [15], [67], [68] | - | - |
Journal of Surgical Research | 3 | [4], [46], [69] | - | - |
Otolaryngol - Head and Neck Surgery | 2 | [50], [55] | - | - |
Journal for Healthcare Quality | 2 | - | [57], [16] | - |
IIE Transactions on Healthcare Systems Eng | 2 | - | - | [1], [61] |
Journal of Pediatric Urology | 2 | [18] | [60] | - |
Archives of Orthopaedic and Trauma Surgery | 2 | [42], [35] | - | - |
American Journal of Obstetrics and Gynecology | 2 | [48], [66] | - | - |
International Journal of Retina and Vitreous | 1 | [49] | - | - |
Revista Brasileira de Enfermagem | 1 | - | - | [63] |
Obstetrics and Gynecoloy | 1 | [64] | - | - |
JAMA Surgery | 1 | - | [56] | - |
AORN Journal | 1 | [65] | - | - |
International Journal of Gynecology and Obstetrics | 1 | [19] | - | - |
Orthopedics | 1 | [44] | - | - |
Journal of Otolaryngology - Head & Neck Surgery | 1 | [54] | - | - |
The Spine Journal | 1 | - | [20] | - |
Surgery | 1 | [52] | - | - |
The Knee Journal | 1 | [43] | - | - |
Journal of the American College of Surgeons | 1 | [38] | - | - |
International Journal of Production Research | 1 | - | - | [34] |
Diseases of the Colon and Rectum | 1 | [70] | - | - |
Journal of Hospital Administration | 1 | [10] | - | - |
Laryngoscope | 1 | - | [58] | - |
CMAJ Open | 1 | [47] | - | - |
Journal of Cardiology & Cardiovascular Therapy | 1 | [53] | - | - |
Annals of Thoracic Surgery | 1 | - | [59] | - |
Journal of Gynecologic Surgery | 1 | [21] | - | - |
European Journal of Operational Research | 1 | - | - | [62] |
Plastic and Reconstructive Surgery | 1 | [17] | - | - |
American Journal of Medical Quality | 1 | - | [22] | - |
Medicine | 1 | [39] | - | - |
Production Planning & Control | 1 | - | [6] | - |
Journal of Minimally Invasive Gynecology | 1 | [51] | - | - |
[1] Ahmad et al. (2019); [4] Malone et al. (2019); [6] Fogliatto et al. (2020); [10] Mhlaba et al. (2015); [15] Avansino et al. (2013); [16] Fogliatto et al. (2018); [17] Humphries et al. (2018); [18] Nast and Swords (2019); [19] Greenberg et al. (2012); [20] Lunardini et al. (2014); [21] Harvey et al. (2017a); [22] Yoon et al. (2018); [34] Cardoen et al. (2015); [35] Tibesku et al. (2013); [37] Siegel et al. (2015); [38] Stockert and Langerman (2014); [39] Capra et al. (2019); [40] Dehann et al. (2014); [41] Hamilton et al. (2013); [42] Kwon et al. (2017); [43] Renson et al. (2014); [44] Hsu et al. (2012); [45] McLawhorn et al. (2015); [46] Farrely et al. (2017); [47] John-Baptiste et al. (2016); [48] Van Meter and Adam (2016); [49] Grodsky et al. (2020); [50] Penn et al. (2012); [51] Harvey et al. (2017b); [52] Morris et al. (2014); [53] Barua and O’Regan (2017); [54] Chin et al. (2014); [55] Crosby et al. (2020); [56] Bush (2007); [57] Farrokhi et al. (2013); [58] Wannemuehler et al. (2015); [59] Cichos et al. (2017); [60] Koyle et al. (2018); [61] Dobson et al. (2015); [62] Dollevoet et al. (2018); [63] Schneider et al. (2020); [64] Bachmann et al. (1998); [65] Ngu (2010); [66] Byrnes et al. (2017); [67] Robinson et al. (2018); [68] Skarda et al. (2015); [69] Dyas et al. (2018); [70] Guzman et al. (2015). |
Stockert and Langerman [38] reported average 13.50% reduction in instruments used in four surgical specialties by combining ITV, observation (OBS), checklists (CL) and chrono-analysis (CA) methods to identify redundant instruments in STs. The authors estimated the processing cost per instrument, which was used in several other STR studies [46–49, 10, 4].
The most widely used technique in STR studies based on EA was the CL, followed by focus groups (FG), OBS and standardization (STD). FG were an important means to motivate multidisciplinary groups to analyze ST rationalization through observation of actual instrument usage, reviewing preference cards, creating educational programs to minimize waste and assessing team motivation after implementation [15, 21, 50–52]. The indicator utilization rate was used by several authors (e.g. [53–55]). Other indicators included sterilization cost, ST weight reduction and OR setup time reduction.
Among studies classified in the LP category, the most cited is Bush [56], followed by Farrokhi et al. [57] and Lunardini et al. [20]. Bush [56] used lean to reduce losses in a large medical center, following Ohno’s seven waste categories (OSW). To reduce errors due to wrong or missing instruments in the assembly of STs, a shadowed instrument tray (SIT) was adopted. Improvement cycles were proposed through kaizen groups (KAI). OSW combined with value stream mapping (VSM) was also the analytical framework adopted by Wannemuehler et al. [58]. They mapped the complete cycle of STs utilization, identifying activities that did not comply with users’ requirements and proposing improvements through KAI, to obtain a 53.85% reduction in instruments in the STs analyzed.
Farrokhi et al. [57] combined OBS, CL, VSM, KAI, Lean 5S (L5S) e STD to analyze back surgery trays. L5S implementation was guided by an interdisciplinary FG with the objective of identifying the usage rate and availability of instruments, as well as those obsolete. New STs were proposed and monitored in the ORs. Two outcomes were reported: reduction of 70% in the number of instruments supplied to the ORs and shorter surgery times. Lunardini et al. [20] combined CL, OBS, STD and KAI to obtain average instrument reduction of 41.45% in STs supplied to the orthopedics specialty. Fogliatto et al. [16, 6] analyzed STs from a larger number of surgical specialties (e.g. ophtalmology, urology, and pediatrics), which were grouped using the closest neighbor algorithm (CAN) and rationalized through a standard operational procedure (SOP) performed within KAI groups. They reported a reduction of 10.78% in instruments over all specialties analyzed. Farrokhi et al. [57], Wannemuehler et al. [58] and Fogliatto et al. [16] analyzed differences in indicators (e.g. waiting times, ST assembly times) before and after rationalization using statistical tests.
The most widely used technique in studies classified in the LP category is CL, followed by FG, KAI and STD. Instrument utilization rate is an indicator frequently reported [59, 60, 22] in the context of VSM, when instruments are categorized as needed (i.e. value-adding) or not needed [57, 58]. Another frequently reported indicator is the satisfaction level of those involved in the rationalization process, which was higher in studies involving multidisciplinary groups and covering several surgical specialties. For example, Koyle et al. [60] and Yoon et al. [22] reported high satisfaction levels with no instruments added to trays after revision; that was not the case in Farrely et al. [46], in which few specialties enrolled in the rationalization effort. In general, reaching consensus among surgical teams increased the observed satisfaction level after ST revision [58].
Among studies classified in the MP category, Dobson et al. [61] is the most cited, followed by Cardoen et al. [34]. Dobson et al. [61] used Modified Integer Linear Programming (PLM) and Heuristics (HEU) to find the composition of STs that minimized costs in the operation of a surgical center, satisfying surgeons’ instrument and scheduling preferences. They reported a reduction of 61.59% in instruments when customizing STs to a particular surgical schedule (although greatly increasing the complexity of ST assembly). Dollevoet et al. [62] modeled the same problem as [61], testing the performance of several heuristics with respect to computational time and quality of the solution provided for short and long planning horizons. Results recommended the use of heuristics for short horizons and of PLM, otherwise. Both studies confirmed better cost reduction performance when a small number of surgical specialties is scheduled to operate on the same day at the surgical center, due to sharing of instruments.
Cardoen et al. [34] optimized the configuration and assignment of STs to surgical procedures using Nonlinear Integer Programming (NIP), CL and HEU. They analyzed (i) the feasibility of using custom packs (CP) of instruments, which may reduce the overall number of items used to perform surgeries but may be unpractical in terms of assembly, and (ii) the increase in sharing of STs among surgical procedures resulting from adding redundant instruments to trays. They addressed the analysis in (i) using HEU. Ahmadi et al. [1] used Mixed Integer Linear Programming (MILP), preference cards (PC) and HEU to configure STs considering ergonomic risks. In opposition to other authors, they reviewed lists of instruments in PCs to identify those obsolete for removal.
Schneider et al. [63] combined techniques belonging to the EA and LP categories (e.g. FG, OBS and BRT) with linear programming (LP) and CAN to review instruments used in 20 ophthalmology procedures and identify infeasibilities in their scheduling in the surgical center. Results included the reduction in the total number of instruments in STs and increase in the number of procedures performed, although numerical figures were not given.
The most frequently used technique in studies classified in the MP category is HEU; all other MP techniques were used at least once. Instrument utilization rate along with availability of personnel, OR, individual instruments and STs were information used in all MP studies [1, 34, 61–63]. When HEU was combined with techniques from other approaches (e.g. EA and LP), the likelihood of solving the ST configuration problem increased.
In Fig. 3 we list operational and economic dimensions that were impacted by ST instrument reduction, as reported by authors from our corpus. Three operational improvements are listed: (i) tray assembly process; (ii) operating rooms (ORs); and (iii) ergonomic functionality associated with the person handling the tray (e.g. size, weight). Three economic improvements are listed: cost reduction in (i) sterilization; (ii) instrument repairs; and (iii) purchases. No article reported all six types of improvements. Within the operational dimension, improvements in ORs were the most frequently mentioned (n = 26). Within the economic dimension, sterilization of instruments (n = 36) and cost reduction with purchases (n = 22) were the most frequently mentioned. Results in Fig. 3 provide the answer to RQ3.
Table 3
Techniques used in each STR approach and percentage of instrument reduction reported
Approach | Author | Technique | Reduction | Approach | Author | Technique | Reduction |
AE | [4] | CL, OBS, STD | 48.00% | AE | [53] | CL, OBS | 39.50% |
AE | [10] | FG, OBS, CA, CT, CP | 61.00% | AE | [54] | CL, FG | 57.00% |
AE | [15] | STD, PC, CL, OBS, FG | NR | AE | [55] | CL | 51.92% |
AE | [17] | CT | NR | AE | [64] | FG, SM, SIT | 33.33% |
AE | [18] | CT, PDSA, FG, RCA, KDD | 38.60% | AE | [65] | PC, FG, CL | 63.74% |
AE | [19] | STD | NR | AE | [66] | CL, STD | NR |
AE | [21] | CL, FG | 19.10% | AE | [67] | STD, PC, OBS | NR |
AE | [35*] | ABC, PSI, ITV | 66.67% | AE | [68] | STD, PC, FG | NR |
AE | [36] | FG, CL | 30.00% | AE | [69] | CL, STD | 63.27% |
AE | [37] | PSI, OBS | 50.00% | AE | [70] | CT | NR |
AE | [38] | OBS, ITV, CL, CA | 13.50% | PL | [6] | FG, CAN, SOP, CL | 10.78% |
AE | [39] | FG, OBS, PSI | 62.11% | PL | [16] | CAN, KAI | 11.00% |
AE | [40*] | CL, PSI | 66.67% | PL | [20] | CL, OBS, STD, KAI | 41.45% |
AE | [41*] | PSI | 62.50% | PL | [22] | FG, CL, SXS | 9.86% |
AE | [42*] | PSI | 54.55% | PL | [26] | STD, PC, CL, OBS, FG | 76.87% |
AE | [43] | PSI | 54.55% | PL | [56] | OSW, SIT, KAI | NR |
AE | [44*] | TDI | 57.14% | PL | [57] | VSM, L5S, STD, OBS, KAI, FG, CL | 70.56% |
AE | [45*] | TDI, DT | 42.86% | PL | [58] | SXS, FG, VSM, KAI, OSW, CL, STD | 53.85% |
AE | [46] | OBS, STD, FG, BRT, CL | 62.30% | PL | [59] | STD, FG, CL | 58.74% |
AE | [47] | CT | 58.00% | PM | [1] | MILP, HEU, PC | NR |
AE | [48] | OBS, CL, CA | 46.67% | PM | [12] | PLM, HEU | NR |
AE | [49] | CL, STD | 89.00% | PM | [34] | CL, HEU, NIP, CP | NR |
AE | [51] | PC, CL, FG | NR | PM | [61] | PLM, HEU | 61.59% |
AE | [52] | NG, PF, RCA, FG, SOP, CL | 20.00% | PM | [63] | BRT, OBS, FG, CAN, LP | 13.10% |
Regarding the operational dimension, improvements in (i) are usually associated with faster processing of trays, from cleaning to assembly, due to smaller number of instruments. That promotes process agility and reduces assembly errors [39]. Although impacting the economic dimension we classified such improvement as operational, since most authors do not report savings associated with the assembly process (an exception is Fogliatto et al. [6]. Improvements in (ii) are related to actions before (open and check STs) and after (replace instruments in STs and check again) the procedure takes place in the OR. There is an economic aspect to this improvement as well; however, most authors associate it with reduction in time to setup [55, 4] and count instruments [38], and errors handling instruments to surgeons [56]. Improvements in (iii) are ergonomic. It is known that weight is one the main risk factors associated with handling of STs [1].
Regarding the economic dimension, improvements in (i) are related to the sterilization of STs and instruments. Rationalized STs are smaller, increasing the number of trays processed in a same autoclave batch and reducing unitary costs [48]. Improvements in (ii) are related to costs with maintenance due to improper placement of instruments on trays and high frequency of sterilization cycles, causing excessive wear [64] and depreciation due to use [53]. Improvements in (iii) are related to purchasing of new or replacement instruments. Manufacturers usually recommend replacement or maintenance of instruments after a given number of sterilization cycles [51]; therefore, reduction in the number of cycles may lead to significant savings [65, 51].
Table 4
– Future research questions associated with STR steps
Step | Research questions |
Prepare | How to raise consensus among multidisciplinary teams to work on rationalization projects? |
How to encourage commitment in rationalization projects? |
Rationalize | What technologies could be explored to manage instruments traceability? |
How can cross-sectional analysis of STs contribute to reducing instruments or STs? |
Implement | What is the best solution to the instruments removed from trays? |
What are the intangible benefits of rationalization STs and how to measure them? |
Which indicators can be used to measure safety of surgical procedures following the rationalization of STs? |
Consolidate | What strategies could be used to consolidate improvements achieved? |
What are relevant future goals to be set by organizations that already have been through an STR cycle? |