Description
The focus topic will be ?Outsourcing Aviation Maintenance and the Correlation in Human Factors?. The review paper must provide an original perspective on the literature, not merely a summary but an extension of knowledge on a topic. Use the attached articles for the research study and references.

The paper should contain these major sections:
1. Statement of the Issue or Problem (1 page)
2. Significance of the Issue / Problem – Why the issue / problem is important to aviation human factors (1 page)
3. Review of Relevant Research (include references to aviation human factors (5 pages)
4. Summary of Major Findings and Conclusions (1 page)
5. Recommendations for future research to address the issue / problem (1 page)

_______________________________________________________________
_______________________________________________________________ Report Information from ProQuest October 23 2016 21:51 _______________________________________________________________
Document 1 of 1
Measuring the Performance of Maintenance Service Outsourcing Author: Cruz, Antonio Miguel; Rios Rincon, Adriana Maria; Haugan, Gregory L ProQuest document link Abstract: ? The aims of this paper are (1) to identif y the characteristics of maintenance service providers that directly impact maintenance service quality, using 18 independent covariables; (2) to quantif y the change in risk these covariables present to service quality, measured in terms of equipment turnaround time (TAT). A survey was applied to every maintenance service provider (n = 19) for characterization purposes. The equipment inventory was characterized, and the TAT variable recorded and monitored for every work order of each service provider (N = 1,025). Finally, the research team conducted a statistical analysis to accomplish the research objectives. The results of this study offer strong empirical evidence that the most influential variables affecting the quality of maintenance service performance are the following: type of maintenance, availability of spare parts in the country, user training, technological complexity of the equipment, distance between the company and the hospital, and the number of maintenance visits performed by the company. The strength of the results obtained by the Cox model built are supported by the measure of the R^sup 2^^sub p,e^ = 0.57 with a value of R^sub p,e^= 0.75. Thus, the model explained 57% of the variation in equipment TAT, with moderate high positive correlation between the dependent variable (TAT) and independent variables. [PUBLICATION ABSTRACT] Links: Linking Service Full text: ? Headnote Abstract The aims of this paper are (1) to identif y the characteristics of maintenance service providers that directly impact maintenance service quality, using 18 independent covariables; (2) to quantif y the change in risk these covariables present to service quality, measured in terms of equipment turnaround time (TAT). A survey was applied to every maintenance service provider (n = 19) for characterization purposes. The equipment inventory was characterized, and the TAT variable recorded and monitored for every work order of each service provider (N = 1,025). Finally, the research team conducted a statistical analysis to accomplish the research objectives. The results of this study offer strong empirical evidence that the most influential variables affecting the quality of maintenance service performance are the following: type of maintenance, availability of spare parts in the country, user training, technological complexity of the equipment, distance between the company and the hospital, and the number of maintenance visits performed by the company. The strength of the results obtained by the Cox model built are supported by the measure of the R^sup 2^^sub p,e^ = 0.57 with a value of R^sub p,e^= 0.75. Thus, the model explained 57% of the variation in equipment TAT, with moderate high positive correlation between the dependent variable (TAT) and independent variables. Keywords Maintenance and Engineering, Hospital; Clinical Engineering; Outsourced Services; Biomedical Engineering; Survival Analysis Introduction The outsourcing of production and maintenance processes has become a frequent practice for many industries. Government, medical devices, and aviation are just a few examples of industries increasingly using outsourcing for maintenance services.1-2 Several factors influence the use of outsourc- ing as an alternative to in-house production or maintenance. Among the most representa- tive are fiscal pressures, contract restrictions, political
forces, bureaucratic routines, and market conditions.3-5 Within the medical engineering field, where the use of outsourc- ing practices has increased not only in terms of the monetary volume of contracts, but also in the quantity of equipment in the charge of contracted maintenance providers, contract- ing maintenance services for medical equipment has become common. In terms of monetary volume, reports indicate that the budget spent on maintenance service contracts is approximately 55% of the total hospital technology management budget.6 Yet while outsourcing practices have grown in popularity, research on outsourcing in academic literature has been contradictory. One published study reported that 34% of companies surveyed believe contractors have high added value in contract maintenance outsourcing.7 Other studies report poor experiences using contracted services. For example, a study conducted across many industries showed that 64% of respondents indicated that they had brought outsourced services back in-house, and 44% did not realize cost savings through outsourcing.8 Another study found that 20-25% of all outsourcing relationships fail within two years, and half fail within five years.9 A broader survey of more than 300 business executives also found the need for improved outsourcing procedures, as only 34% of executives were satisfied with contracted service providers.10 These findings suggest a gap between client needs and contractor performance, prompting many studies to tackle the problem of crucial elements related to outsourcing processes, including mainte- nance. For example, many authors have focused their research on the development of mathematical models for maximizing not only the contractor’s profit, but also the total profit of the outsourcing system.11-15 Another approach focuses on the learning effects in both production and maintenance outsourc- ing, understanding the learning effects as a phenomenon that decreases unit production time or cost as additional units are produced. In the literature on maintenance, two papers are significant. Finally, considerable theoretical and anecdotal work has focused on managing the contract performance of outsourced services in maintenance and production processes, hypothesizing that both contractual completeness and strategic evaluation have significant positive effects on overall outsourcing performance.16 These hypotheses are based on the postulate that writing detailed contracts reduces the risk of contract failure and thus lowers the transac- tion costs inherent in negotiating, implementing, and monitoring a contract relationship.17 But if firms do not conduct any evaluation, they run the risk of outsourcing the wrong activities or functions, and thus may reduce their competitiveness. Still, the results obtained from previous studies indicate that the evaluation of outsourcing performance merits deeper evaluation, as no statistical evidence was found to support the hypotheses that contractual completeness and strategic evaluation have positive effects on outsourc- ing performance.3 The healthcare industry, in which the efficient performance of maintenance service providers for medical devices has direct implications for patient care, has much to gain from such research. In addition to affecting costs and patient waiting times, the unavail- ability of medical devices has an inherent risk for patients. Thus, maintenance service must be done in a timely and competent manner. Yet in spite of the importance of the matter, healthcare institutions continue to lack adequate methods for evaluating the perfor- mance of maintenance service providers. In many cases, the information required to complete such studies is simply unavailable, while the issues that influence contract service provider performance are neither known nor measured. Thus, a comprehensive contractual completion and an intensive strategic evalua- tion of contracts cannot always be performed. It has been reported that the variables used to evaluate outsourcing performance are a composite of those that give useful informa- tion related to annual cost,17 service quality, responsiveness or flexibility, and reliability, relative to expectations.1 In relation to the responsiveness of maintenance service providers, three variables are particularly important for monitoring performance, including: response time (RT),1 service time (ST),2 and turnaround time of equipment3 (TAT).19 The performance of maintenance service providers, including lower values of RT, ST and TAT,4 not only depends on the hypotheses developed by Handley and Benton,18 but also on the capacity of the firm to deliver the service, dependent on firm and human resources features (G1: HR-FF); the features of services they offer (G2: FServ); type of contractual relationships (G3: CRS); and the equipment
features under their charge (G4: CEq) (Figure 1). This paper tries to fill the gap in the current evaluation methods of maintenance service provider performance in healthcare institutions. Specifically, the two objectives of this work are: 1. To determine which variables from variable groups G , G , G , and G have a 1 2 3 4 significant influence on the TAT indicator. To build a Cox proportional hazard model to determine quantitatively which of the independent variables in the groups G1, G2, G3, and G4 have a significant influence on the increase or decrease in the probability of higher or lower values of the TAT variable. This study contributes to the clinical engineering field in several fundamental ways. First, the results have the potential to substantially enhance the strategic evaluation processes for maintenance outsourcing in the healthcare industry. Although the variables in groups G1, G2, G3, and G4 (see Methods) for completing an adequate characterization of maintenance service providers were recommended by ECRI,6 there is no current consensus as to which- and to what extent-these variables influence performance of maintenance service provid- ers. Therefore, strategic evaluation processes are difficult to implement because managers do not know which variables to include, nor how to weigh the influence of the variables to make decisions. Second, contractual completeness of outsourcing in the healthcare industry also will benefit. Once the impact of the variables on the TAT indicator is known, medical engineering departments can write better, more detailed contracts, reducing the risks of contract failure, and thus cutting costs and reducing the risks to the downtime of a healthcare institution’s medical devices. Third, this study will be valuable for healthcare institutions in developing coun- tries, where contracting maintenance services often is inevitable because hospitals have fewer properly trained employees on staff, and lack material resources to handle these functions on their own. Additionally, this study creates a methodol- ogy for monitoring and evaluating the performance of maintenance service providers using statistical analysis, helping managers make better decisions about which variables to include in future strategic evaluation and contract completion processes. To the knowledge of the authors, the problem of quantitatively determining the independent variables in groups G1, G2, G3, and G4 with a significant influence on the values of the TAT variable have not been empirically explored in the existing health- care industry literature. Contextual Issues Regarding the Structure of the Colombian Healthcare System and the Maintenance Modalities of Medical Devices Healthcare services in Colombia are deliv- ered through a complex system which revolves around the General System for Social Security in Healthcare (SGSSS) which consists of two main components, run by the federal government: the Contribution System (RC) and the Subsidy System (RS). The RS affiliates those who are unable to pay the monthly healthcare payroll deduction (such as those earning salaries below the legal mini- mum wage of U.S. $249 per month), while the RC affiliates formally employed workers capable of making this contribution, typically between 4-8% of their monthly wage. In 2010, the RC and RS provided coverage to 39.7% and 51.4% of the total population, respectively. For the delivery of healthcare services, the system rests upon two fundamental pillars: (1) the insurance providers, which may be either public or private entities which insure the population and act as intermediaries between the State and medical service providers. These are called healthcare service promoters, known by the Spanish acronym, EPS. (2) The healthcare service providers (known by the Spanish acronym, IPS) include the hospitals, clinics, and laboratories that provide direct healthcare services to users, who pay directly for these services in order to obtain higher quality care than may be available under the SGSSS.20 According to a report by the Ministry of Social Protection, total healthcare expendi- tures as a percentage of GDP average 8.5% during the period between 1993 and 2003. On the other hand, during the same period, the percentage of healthcare expendi- tures corresponding directly
to medical services was 66.2%, while 17% went to administrative costs, 8% corresponded to healthcare investments, and 8.8% to other costs.20 According to the country’s Special Registry of Health Service Providers (REPSS), there were a total of 46,358 health- care providers (IPS and EPS) in 2010. Of these, 10,390 were IPS (9,277 private and 1,113 public), 34,933 were independent professional medical specialists, 341 were special medical transportation companies (ambulances), and 694 corresponded to other medical services. In total, this represents a capacity of approximately 68,000 hospital beds, or approximately 1.5 beds per 1,000 inhabitants.20 In terms of human resources, according to the Center for Development Projects at the Universidad Javeriana of Colombia (CENDEX), in 2010 there were approximately 226,600 professionals working in the Colombian healthcare sector, of which 77,000 were doctors, corresponding to 1.7 doc- tors per 1,000 inhabitants. Specifically relating to the specialty of biomedical engineering, in 2011 there were a total of 1,500 engineers and technicians working in the field.21 At a rate of 0.033 per 1,000 inhabitants, that figure is evidence that the human resources in this field are insufficient for the needs of the country. With respect to the maintenance of medical devices in Colombia, there have been three traditional methods for providing equipment maintenance service, including: in-house service by the clinical or biomedical department, the original equipment manu- facturer (OEM), and third party (TP) or independent service organizations (ISOs).21 Obviously, outsourced maintenance services are provided by the OEM and TP, which sometimes share service tasks with a hospi- tal’s in-house service department. Maintenance service by the OEM may be on-demand or under contract-during or after warranty-and requires overseeing the quality of the maintenance service performed. A TP is used when the OEM delegates its maintenance service to one. A TP has the same requirements as those of the OEM, with respect to monitoring and quality measure- ment of maintenance service performance. Providing a full characterization of mainte- nance service provider and the maintenance modalities (i.e., outsourced or in-house) in the Colombian context is out of the scope of this paper. Still, some scholars have reported that this market is characterized by, (1) a high level of maintenance outsourcing services in hospitals, in some cases more than 62.23% of the total medical inventory; (2) the mainte- nance service providers are companies that can be catagorized as experienced (i.e., with an average value of 25 years of experience in the industry) and small (i.e., human resources total of three personnel, including technicians and engineers); (3) with poor infrastructure to provide maintenance services. For example, Cruz et. al22 found that 15.38% of maintenance service providers had no equipment replacement stock held in the country and 11.50% did not offer online assistance. In addition, the same study found poor maintenance service provider perfor- mance, characterized by high turnaround time values for medical devices, with an extreme TAT value of 101 days; and an average value of 9.79 days. In Colombia, hospital administrators face many challenges when deciding whether to outsource maintenance services. For exam- ple, when hospitals purchase highly complex equipment and the OEM refuses to allow other maintenance organizations (i.e., ISO) access to products such as online diagnostic programs and/or very specific spare parts, hospitals become locked into maintenance contracts with the OEM to gain access to such services, driving costs above what they would be in a competitive environment. Additionally, TP maintenance providers often lack the ability to invest in such idiosyncratic assets due to the high costs involved in using highly specialized parts and the additional cost of keeping parts in storage. Parts are thus ordered on an on- demand basis from an external supplier, such as the OEM, resulting in longer equipment turnaround time. If the OEM does not have a formal policy of supporting other maintenance companies, it may view other companies as competitors with respect to its own equipment mainte- nance business and thus delay or block the sale of specific spare parts. Research Methods This study was conducted in a public hospi- tal, of “high-level complexity,” according to the Colombian Ministry of Health hospital classification, with three full-time equivalent biomedical technicians in its clinical engi- neering department. The hospital has an average of 245 licensed beds, with a total of 1,050 medical devices in its
inventory. The total inventory value (in Colombian pesos) is about $24,101,821,107 (i.e., approximately U.S. $12,050,910), with an average of service cost versus acquisition cost ratio of 8.7%.19 For the equipment inventory, the average value of the equipment’s usage time versus useful life versus usage time ratio was 0.86. The authors of this paper followed the methodology proposed by Miguel et. al.20 First, a study characterizing the hospital’s inventory was conducted. The main goals were to determine the state of the equipment inventory and to determine which medical devices were under outsourced maintenance service. Equipment variables for inventory characterization were monitored in nine pilot areas5 in the hospital under study. One hundred percent of the devices in the pilot areas were included in the data sample (N= 264). For the purposes of this study, the most important variables are the equipment level of obsolescence (Obsolec), calculated as the ratio of equipment use time, in years (UT) to useful life, in years (UL). Particularly, the UT over UL ratio was operationalized as follows: If the UT/UL ratio is lower than one (UT/ UL<1), the equipment is not obsolete. If the ratio is greater than one (UT/UL>1), the equipment is obsolete because it has passed what the OEM considers to be its useful life. We coded technological obsolescence as “NO” if the value of the UT/UL ratio was less than one, while obsolete equipment with UT/ UL ratios of greater than one were coded as “YES”. This transformation from a ratio to binary scale for this variable has proven feasible in many applications to measure the obsolescence of medical devices.22 The technical complexity of equipment was measured in categories of high, medium, and low complexity (Complex). Finally, the equipment types (EqTypes) included were Diagnostics, Treatment, Monitoring, Support, and Laboratory.23 Next, a survey was designed and conducted to characterize maintenance service provid- ers (n=19). A total of 18 variables were studied, including the following: contract duration, in years (ConDur); total quantity of equipment included in the contract (NEquip); maintenance type (MaintType); whether the contract is a warranty maintenance contract (ContRel); whether the maintenance service provider has replacement parts in the country where the service is offered (RepParCount); whether the contract includes replacements parts (REParts); the number of annual visits stipulated in the contract (NvisitYear); equipment types involved in the maintenance service contract (EqTypes); number of engineers and technicians working on the contract (TotalHumResContract); experience of the company’s human resources, in years (ExpPersonalYear); distance of the service provider from the hospital, in kilometers (HospDist); quantity of contracts managed by the service provider(TotNumContracts); experience of the company in the industry, in years (ExpCompany); whether remote diagnostic for both maintenance and correc- tive services are offered (ServLine); and whether training is provided to equipment users, operators, and technicians (UserTrain- ing and TechTraining); and finally, the technical complexity (Complex) and level of obsolescence (Obsolec) of equipment involved in every maintenance transaction. All independent variables for both inventory and maintenance service provider characteri- zation were then classified into groups. Group 1 (G : HR-FF) included variables 1 measuring service provider and human resource features; Group 2 included the service features they offer (G : FServ); Group 3 included variables measuring the type of contractual relationships (G : CRS); and last, Group 4 measured the equipment features under their charge (G : CEq) (for more details see column 2 of Table 1). Next, the research team monitored each service provider for the turnaround time (TAT) variable (i.e., the dependent variable), using the work orders of every corrective and scheduled maintenance task the service provider performed over a six-month period (N=1,025). Normally TAT is defined as the time from service request until the equip- ment is back up and running. As both response time and downtime of maintenance service provider is included in TAT, we decided to use TAT as dependent variable instead of the time that equipment is unavail- able due to repair or preventive maintenance, i.e. downtime. The authors of this research believe that TAT is a more comprehensive indicator than others (i.e. downtime, in hours), because it directly relates to the availability of medical devices (i.e. lower values of medical device TAT means lower values of availability6) making it an appropri- ate indicator of maintenance performance. Obviously, the timeframe for TAT calculation differs if the work order is preventive or corrective.24
Next, a descriptive statistical analysis was conducted for all variables. Each variable from groups G1, G2, G3 and G4 was catego- rized into dummy (YES=1 or NO=0) or categorical variables (see column 3 of Table 1). This categorization allowed us to conduct statistical tests8 between the variable catego- ries in groups G1, G2, G3 and G4 and the TAT values for each category (see column 5, i.e. Log Rank Test of Table 1). Where these tests produced significant results (i.e., p value <0.05), we concluded the variables from groups G1, G2, G3 and G4 have influence on the TAT of maintenance service providers. As shown in Table 1, most tests for these variables produced significant results. Thus, the next step was to quantify the relationship between variables in groups G1, G2, G3 and G4 and TAT. To do that, a Cox proportional hazard model was built. In this model, variables of groups G1, G2, G3 and G4 are called co- variables. The methodology fol- lowed to build the model was proposed by Hosmer.25 The elimination or inclusion of covariables in the Cox model is a combina- tion of expertise, with support from contingence tables to eliminate problematic multicollinearity, and the patience of the data analysts. Finally, an assessment of the Cox model's adequacy was conducted (see results for more details). Results Table 1 shows the results of the statistical tests, as a necessary step before building the Cox model, between categories of independ- ent variables of groups G1, G2, G3, and G4, and TAT. Table 2 gives the estimated coefficients for the Cox proportional hazards model containing significant variables (p <0.05). The statistical tests between the categories of independent variables in groups G1, G2, G3, and G4, and TAT showed in Table 1, provide highly significant values at p <0.05, and in many cases at p <0.01. In addition, the medians of TAT for each co-variable category calculated by Kaplan-Meier method using the Log Rank test exhibit different values and provide highly significant values at p <0.05, and in most cases at p <0.01. Therefore, we found statistically significant evidence (p-values <0.05) to support that 17 of 18 of our variables studied have an impact on mainte- nance performance of service providers, i.e., TAT (Table 1). The Cox model found that the subset of significant variables that determine the quantitative relationship in terms of increase or decrease in risk for higher or lower values of TAT in function of variables in groups G1, G2, G3, and G4 were: whether the mainte- nance service providers have replacements parts in the country the service is offered (RepParCount (G )); distance of the service 1 provider from the hospital, in kilometers (HospDist (G )); the number of annual visits 1 stipulated in the contract, including both preventive visits (NvisitYear (G )); whether training is provided to users (UserTraining (G )); maintenance type (MaintType (G )); 23 and technical complexity of equipment (Complex (G )) (see Table 2 for more details). 4 Discussion and Managerial Implications The managerial implications of this research are intended to determine which variables should be included in the evaluation, selection, and contract formulation processes of purchasers of outsourced maintenance services in the field of medical device mainte- nance contracts. This in turn should help to obtain better contractual completeness results. It is true that the "contract alone is not sufficient to align objectives and mitigate external sourcing risks"3 and to obtain better performance of maintenance service provid- ers. However, in developing countries, where a lack of standardized contracting proce- dures, methodologies, and variables to measure the performance of maintenance service providers is common, the determina- tion of the variables that impact performance and the respective inclusion of penalties in the contract are very important issues that deserve to be studied. From a managerial perspective, our results lead to a number of implications for the selection and negotiation processes with medical device maintenance service provid- ers. Some of the most important are: 1. We found that the higher the geographical distance between the maintenance service provider, the higher the TAT values. Our suggestion here is, whenever possible, ensure that the maintenance service provider has the technical capability to provide the service using either a diagnos- tic remote service or through the adoption of Help Desk concept service. During the negotiation process, make sure that maintenance service providers have
invested in ancillary telecommunication infrastructure to incorporate and extend the maintenance support of medical devices at distances geographically sepa- rate from maintenance service providers. 2. We also found higher TAT values when the maintenance service provider did not have equipment parts in the same country in which maintenance service was provided. Our suggestions here are: (a) negotiate at least a 10-year post-warranty provision of critical parts with the equipment vendor at the time of purchase, and establish channels with the OEM for subsequent purchases of spare parts; (b) whenever possible, for both clinical engineering departments and government healthcare systems, create a specific internal depart- ment (e.g., National Physical Asset Management Bodies) responsible for the supply of medical equipment spare parts, especially for low-income countries; (c) during the selection process, identify the best maintenance service providers, in terms of efficiency, speed, and quality for spare parts delivery. 3. We found that TAT is lower if the mainte- nance service provider includes some specific repair parts in the contract agreement. The advice here is, whenever possible during the negotiation phase, ensure the inclusion of necessary terms and conditions in contracts with mainte- nance service providers in order to guarantee the inclusion in the contract of parts crucial to the maintenance tasks. Some maintenance service providers abuse their competitive advantage because they are the exclusive providers of very specific spare parts, leading to low perfor- mance. However, such a practice damages their reputation and may result in hospital managers switching to a competitor. 4. Our research shows that if maintenance service providers use remote diagnostic tools during maintenance tasks the TAT is lower. Our suggestion here is that when buying high technology equipment, hospitals should negotiate the purchase of software diagnostic tools directly with the OEM at the time of equipment purchase whenever possible. By negotiating the purchase of these auxiliary tools at the time of equipment purchase, hospitals may increase their leverage over the OEM, which otherwise might be unlikely to relinquish exclusive control over such software. 5. We found the higher the number of preventive maintenance visits per year, the higher the TAT. Therefore, managers of clinical engineering departments need to control preventive maintenance frequency in order to optimize equipment availability. While some maintenance service providers offer unlimited preventive maintenance visits per year as a competitive advantage, high preventive maintenance frequency actually reduces equipment availability, increasing the TAT. Therefore, it is impor- tant for managers of clinical engineering departments to balance the need for preven- tive maintenance to keep equipment from breaking down, with the risk that excessive preventive maintenance needlessly increases equipment TAT. We recommend following the maintenance frequency suggested by the manufacturer of the equipment. Only in cases where there is sufficient statistical evidence for increasing maintenance frequency should mainte- nance frequency be changed. However, before doing so, the manager of the clinical engineering department should consider multiple factors (e.g., the regulatory environment, the physical environment, the reliability of the equipment, how much wear the equipment receives during normal use, etc.) The analysis of all these factors that lead to the modification to the mainte- nance frequency should be presented to a multidisciplinary safety committee or hospital quality management commission to make the final decision. 6. Our study suggests that for some medical devices, high preventive maintenance frequency (more than six visits per year) may be necessary. Therefore, it is recom- mended whenever possible to take a variety of approaches to reduce TAT, including: (a) schedule all maintenance tasks of equip- ment located at the same clinical location (e.g. emergency care unit, operating rooms, or clinical laboratory) at the same time, or (b) to schedule all the maintenance tasks for all equipment of a given type (e.g. defibrilla- tors, electrocardiographs) at the same time. Equipment located in the same areas generally have the same level of complexity and risk; thus, these strategies should not be difficult to implement. 7. We found that if maintenance service providers do not provide training to users and technicians, there is a negative impact on TAT. While this result seems obvious, many low-income countries face problems with
medical device operation and mainte- nance due to a lack of training. Our suggestions follow: Make sure that maintenance service providers have proper continuing education programs for both users and biomedical technicians. User training programs should focus on proper operation of medical devices, daily mainte- nance, and fault reporting symptoms of technical systems. As medical device users are on the frontline of patient care, they play a fundamental role in identifying and reducing potential medical device prob- lems that could lead to patient injury. On the other hand, technician training programs should be focused on identifica- tion of the training strategies for every type of technician profile, whether oriented or problem solving. Whenever possible, provide continu- ing training in factories in which the equipment has been designed and assem- bled. The inclusion of these facilities as an “aggregate value” to service can increase service quality reputation. During the service provider selection process, the quality of a provider’s training packages should be taken into account in the analysis. (4) Be aware of proper inclusion of clauses in the contract that ensure training to both users and techni- cians. Maintenance service providers that do not offer this possibility should be eliminated from the selection process. 8. The results of this research showed that the higher the contract duration, the higher the TAT. We strongly suggest making one-year base arrangements in order to monitor the maintenance service provider’s performance, especially in cases where the healthcare institution lacks basic contracting skills, or does not have the possibility to completely verify the techni- cal capability of the maintenance service providers either at the time of contract signing or during contract running. Limitations and Opportunities For Future Research This study can be improved in many ways. The data sample hospitals and maintenance service providers should be increased, while at the same time new covariables should be included in future studies. Increasing the number of hospitals and maintenance service providers in the data sample would provide more generalized results in the effects of covariables in groups G1, G2, G3, and G4 in the TAT. The inclusion of new co-variables in the Cox model, such as the type of healthcare institution (public or private), the contract cost, the priority ranking (high, medium or low), the medical service type (imaging, surgery, emergency, etc.), the weather conditions, the road infrastructure, whether penalties in the contract are established, and the time that the healthcare institution takes for releasing pay orders deserve to be studied for their potential impact on TAT. Conclusions It has been pointed out that outsourcing and outsourcing performance alters the risk profile of the supply chain.3 The results obtained in this study offer strong empirical evidence for this finding. This is the main contribution that this paper makes. From this research, the authors can conclude that: 1. The capacity of the firm to render its services (firm and human resources features) (G : HR-FF); the features of services they offer (G : FServ); type of contractual relationships (G : CRS); and 3 finally, the equipment features under their charge (G : CEq) have an impact on a maintenance service provider’s perfor- mance (TAT, alters the risk profile of supply chain). This is supported by the measure of the R2 = 0.57, with a value of R = 0.75 of p,e p,e the Cox model built. Thus, it can be said that covariables account for 57% of the variation in the TAT variable, with moderate high positive correlation between covari- ables (independents) and the dependent variable (TAT) (i.e. the R2 = 0.57). p,e The Cox model built allowed the research team to find the most significant variables that affect the maintenance service providers’ performance (TAT). These are the distance of the service provider from the hospital, in kilometers (Km) (HospDist (G )); whether the maintenance service 1 provider has replacement parts in the country the service is offered (RepParCount (G )); whether training is provided to equipment users (UserTraining (G )); mainte- nance type (MaintType (G )); technical complexity of equipment (Complex (G )); and the number of annual 4 preventive maintenance visits stipulated in the contract (NvisitYear (G )). n Acknowledgment
We would like to thank COLCIENCIAS for the resources provided in Grant Announcement 459/08, which financed this study. Thanks to Sandra Usaquen Perilla and Nidia Nelly Vanegas Pab?n who helped in the data collection phase of our research. Thanks also to University Hospital La Samaritana for its support and collaboration in completing this study. Finally, thanks to Milciades Iba?ez Pinilla for his advice on the statistical model selection in the beginning stages of this project. Sidebar The results obtained from previous studies indicate that the evaluation of outsourcing performance merits deeper evaluation, as no statistical evidence was found to support the hypotheses that contractual completeness and strategic evaluation have positive effects on outsourcing performance. This study creates a methodology for monitoring and evaluating the performance of maintenance service providers using statistical analysis, helping managers make better decisions about which variables to include in future strategic evaluation and contract completion processes. References References 1. Tarakci H, Tang K and Teyarachakul S. Learning Effects on Maintenance Outsourcing. European Journal of Operational Research. 2009;192:138-150. 2. Greene J. How Much Privatization? A Research Note Examining the Use of Privatization by Cities in 1982 and 1992. Policy Studies Journal. 1996;24(4):632-640. 3. Benton J. And Menzel J. Contracting and Franchising: County Services in Florida. Urban Affairs Quarterly. 1992;27:436-456. 4. Carver R. Examining the Premises of Contracting Outsourcing. Public Productivity and Management Review. 1998;8:27-40. 5. Hirsch W. Privatizing Government Services: An Economic Analysis of Contracting Out by Local Governments. 1991. Los Angeles: University of California. 6. ECRI. Types of Services: Their Advantages and Disadvantages. Health Technology. 1989;3(4):9-20. 7. Jensen D. Contract Worker Services: An Inside View. Aviation Management. 2006. Available at: www.aviationtoday.com/am/ categories/bga/Contract-Worker-Services-An-Inside-View_6139. html#.US99- 2e3XEM. Accessed Feb. 27, 2013. 8. Landis K, Mishra S and Porrello K. Calling a Change in the Outsourcing Market: The Realities for the World’s Largest Organizations. 2005. Deloitte Consulting Report. 9. Doig S, Ritter R, Speckhals K, and Woolson D. Has Outsourcing Gone Too Far? McKinsey Quarterly. 2001:24-37. 10. Robinson P, Lowes P, Loughran C, Moller P, Shields G, and Klein E. Why Settle for Less? Outsourcing Report. 2008. Deloitte Consulting Report. 11. Murthy D and Asgharizadeh E. Optimal Decision Making in a Maintenance Service Operation. European Journal of Operational Research. 1999;116:259-273. 12. Asgharizadeh E and Murthy DNP. Service Contracts: A Stochastic Model. Mathematical and Computer Modelling. 2000;(31):11-20. 13. Plambeck E. And Zenios S. Performance-Based Incentives in a Dynamic Principal-Agent Model. Manufacturing and Service Operations Management. 2000;2:240-263. 14. Tarakci H, Tang K, Moskowitz H, and Plante R. Incentive Maintenance Outsourcing Contracts for Channel Coordination and Improvement. IIE Transactions. 2006a;38:671-684. 15. Tarakci H, Tang K, Moskowitz H, and Plante R. Maintenance Outsourcing of a Multiprocess Manufacturing Dystem with Multiple Contractors. IIE Transactions. 2006b; 38:67-78.. 16. Wang K. and Lee W. Learning curve analysis in total productive maintenance. The International Journal of Management Science. 2001;29:491-499.
17. Trevor L. And Potoski M. Managing Contract Performance: A Transaction Costs Approach. Journal of Policy Analysis and Management. 2003;22(2): 275-297. 18. Handley SH and Benton WC. Unlocking the Business Outsourcing Model. Journal of Operations Management. 2009;27(5): 344-361. 19. Cohen T. Benchmark Indicators for Medical Equipment Repair and Maintenance. BI&T. 1995; 29(4): 308- 320. 20. Guerrero R, Gallego AI, Becerril-Montekio V, and V?squez J. Sistema de Salud de Colombia. Salud P?blica de M?xico. 2011;53(2): 144-155. 21. Rios-Rincon AM, Miguel CA, Rodriguez CHLE, and Chaparro J. La Ingenier?a Biom?dica en Colombia: Una Perspectiva desde la formaci?n del Pregrado. Revista Ingenier?a Biom?dica. 2010; 4(7):23-43. 22. Cruz AM, Perilla S, and Pab?n N. Clustering Techniques: Measuring the Performance of Contract Service Providers. IEEE Eng Med Biol Mag. 2010;29(2):119-26. 23. Invima. Decreto 4725 de 2005. Invima, Available by password at: www.minproteccionsocial.gov.co/VBeContent/library/documents/ DocNewsNo15472DocumentNo2802.PDF.Accessed Feb. 27, 2013. 24. Cruz AM, Rodr?guez D, S?nchez V, Pozo Pu?ales ET, and Vergara Perez I. Measured Effects of User and Clinical Engineer Training Using a Queuing Model. BI&T. 2003;37(6):405-421. 25. Hosmer WH. Applied Survival Analysis Regression Modeling of Time-to-Event Data. 2nd Edition. Wiley Series in Probability and Statistics. New Jersey. 2008. AuthorAffiliation About the Authors Antonio Miguel Cruz, PhD, is a nuclear engineer with the School of Medicine and Health Sciences at the Universidad del Rosario in Bogot?, Colombia. E-mail: antonio.miguel@urosario.edu.co Adriana Maria Rios Rincon, MSc, is an occupational therapist with the school. E-mail: adriana.rios@ urosario.edu.co Gregory L. Haugan, BA, is a research assistant with the school. E-mail: haugangl@ gmail.com MeSH: Equipment & Supplies, Hospital, Hospital Departments, Humans, Models, Statistical, Program Evaluation, Biomedical Engineering — organization & administration (major), Biomedical Engineering — standards (major), Maintenance — methods (major), Maintenance — standards (major), Outsourced Services (major) Publication title: Biomedical Instrumentation & Technology Volume: 47 Issue: 6 Pages: 524-35 Number of pages: 12 Publication year: 2013 Publication date: Nov/Dec 2013 Year: 2013 Section: Columns and Departments Publisher: Allen Press Publishing Services Place of publication: Philadelphia
Publication subject: Medical Sciences ISSN: 08998205 Source type: Scholarly Journals Language of publication: English Document type: Feature, Journal Article Document feature: Diagrams Tables References Accession number: 24328978 ProQuest document ID: 1471052019 Document URL: http://search.proquest.com.ezproxy.libproxy.db.erau.edu/docview/1471052019?accountid=27203 Copyright: Copyright Allen Press Publishing Services Nov/Dec 2013 Last updated: 2014-02-19 Database: ProQuest Central,ProQuest Advanced Technologies & Aerospace Collection
_______________________________________________________________ Contact ProQuest Copyright ? 2016 ProQuest LLC. All rights reserved. – Terms and Conditions

Leave a Reply

Your email address will not be published. Required fields are marked *

Description
The focus topic will be ?Outsourcing Aviation Maintenance and the Correlation in Human Factors?. The review paper must provide an original perspective on the literature, not merely a summary but an extension of knowledge on a topic. Use the attached articles for the research study and references.

The paper should contain these major sections:
1. Statement of the Issue or Problem (1 page)
2. Significance of the Issue / Problem – Why the issue / problem is important to aviation human factors (1 page)
3. Review of Relevant Research (include references to aviation human factors (5 pages)
4. Summary of Major Findings and Conclusions (1 page)
5. Recommendations for future research to address the issue / problem (1 page)

_______________________________________________________________
_______________________________________________________________ Report Information from ProQuest October 23 2016 21:51 _______________________________________________________________
Document 1 of 1
Measuring the Performance of Maintenance Service Outsourcing Author: Cruz, Antonio Miguel; Rios Rincon, Adriana Maria; Haugan, Gregory L ProQuest document link Abstract: ? The aims of this paper are (1) to identif y the characteristics of maintenance service providers that directly impact maintenance service quality, using 18 independent covariables; (2) to quantif y the change in risk these covariables present to service quality, measured in terms of equipment turnaround time (TAT). A survey was applied to every maintenance service provider (n = 19) for characterization purposes. The equipment inventory was characterized, and the TAT variable recorded and monitored for every work order of each service provider (N = 1,025). Finally, the research team conducted a statistical analysis to accomplish the research objectives. The results of this study offer strong empirical evidence that the most influential variables affecting the quality of maintenance service performance are the following: type of maintenance, availability of spare parts in the country, user training, technological complexity of the equipment, distance between the company and the hospital, and the number of maintenance visits performed by the company. The strength of the results obtained by the Cox model built are supported by the measure of the R^sup 2^^sub p,e^ = 0.57 with a value of R^sub p,e^= 0.75. Thus, the model explained 57% of the variation in equipment TAT, with moderate high positive correlation between the dependent variable (TAT) and independent variables. [PUBLICATION ABSTRACT] Links: Linking Service Full text: ? Headnote Abstract The aims of this paper are (1) to identif y the characteristics of maintenance service providers that directly impact maintenance service quality, using 18 independent covariables; (2) to quantif y the change in risk these covariables present to service quality, measured in terms of equipment turnaround time (TAT). A survey was applied to every maintenance service provider (n = 19) for characterization purposes. The equipment inventory was characterized, and the TAT variable recorded and monitored for every work order of each service provider (N = 1,025). Finally, the research team conducted a statistical analysis to accomplish the research objectives. The results of this study offer strong empirical evidence that the most influential variables affecting the quality of maintenance service performance are the following: type of maintenance, availability of spare parts in the country, user training, technological complexity of the equipment, distance between the company and the hospital, and the number of maintenance visits performed by the company. The strength of the results obtained by the Cox model built are supported by the measure of the R^sup 2^^sub p,e^ = 0.57 with a value of R^sub p,e^= 0.75. Thus, the model explained 57% of the variation in equipment TAT, with moderate high positive correlation between the dependent variable (TAT) and independent variables. Keywords Maintenance and Engineering, Hospital; Clinical Engineering; Outsourced Services; Biomedical Engineering; Survival Analysis Introduction The outsourcing of production and maintenance processes has become a frequent practice for many industries. Government, medical devices, and aviation are just a few examples of industries increasingly using outsourcing for maintenance services.1-2 Several factors influence the use of outsourc- ing as an alternative to in-house production or maintenance. Among the most representa- tive are fiscal pressures, contract restrictions, political
forces, bureaucratic routines, and market conditions.3-5 Within the medical engineering field, where the use of outsourc- ing practices has increased not only in terms of the monetary volume of contracts, but also in the quantity of equipment in the charge of contracted maintenance providers, contract- ing maintenance services for medical equipment has become common. In terms of monetary volume, reports indicate that the budget spent on maintenance service contracts is approximately 55% of the total hospital technology management budget.6 Yet while outsourcing practices have grown in popularity, research on outsourcing in academic literature has been contradictory. One published study reported that 34% of companies surveyed believe contractors have high added value in contract maintenance outsourcing.7 Other studies report poor experiences using contracted services. For example, a study conducted across many industries showed that 64% of respondents indicated that they had brought outsourced services back in-house, and 44% did not realize cost savings through outsourcing.8 Another study found that 20-25% of all outsourcing relationships fail within two years, and half fail within five years.9 A broader survey of more than 300 business executives also found the need for improved outsourcing procedures, as only 34% of executives were satisfied with contracted service providers.10 These findings suggest a gap between client needs and contractor performance, prompting many studies to tackle the problem of crucial elements related to outsourcing processes, including mainte- nance. For example, many authors have focused their research on the development of mathematical models for maximizing not only the contractor’s profit, but also the total profit of the outsourcing system.11-15 Another approach focuses on the learning effects in both production and maintenance outsourc- ing, understanding the learning effects as a phenomenon that decreases unit production time or cost as additional units are produced. In the literature on maintenance, two papers are significant. Finally, considerable theoretical and anecdotal work has focused on managing the contract performance of outsourced services in maintenance and production processes, hypothesizing that both contractual completeness and strategic evaluation have significant positive effects on overall outsourcing performance.16 These hypotheses are based on the postulate that writing detailed contracts reduces the risk of contract failure and thus lowers the transac- tion costs inherent in negotiating, implementing, and monitoring a contract relationship.17 But if firms do not conduct any evaluation, they run the risk of outsourcing the wrong activities or functions, and thus may reduce their competitiveness. Still, the results obtained from previous studies indicate that the evaluation of outsourcing performance merits deeper evaluation, as no statistical evidence was found to support the hypotheses that contractual completeness and strategic evaluation have positive effects on outsourc- ing performance.3 The healthcare industry, in which the efficient performance of maintenance service providers for medical devices has direct implications for patient care, has much to gain from such research. In addition to affecting costs and patient waiting times, the unavail- ability of medical devices has an inherent risk for patients. Thus, maintenance service must be done in a timely and competent manner. Yet in spite of the importance of the matter, healthcare institutions continue to lack adequate methods for evaluating the perfor- mance of maintenance service providers. In many cases, the information required to complete such studies is simply unavailable, while the issues that influence contract service provider performance are neither known nor measured. Thus, a comprehensive contractual completion and an intensive strategic evalua- tion of contracts cannot always be performed. It has been reported that the variables used to evaluate outsourcing performance are a composite of those that give useful informa- tion related to annual cost,17 service quality, responsiveness or flexibility, and reliability, relative to expectations.1 In relation to the responsiveness of maintenance service providers, three variables are particularly important for monitoring performance, including: response time (RT),1 service time (ST),2 and turnaround time of equipment3 (TAT).19 The performance of maintenance service providers, including lower values of RT, ST and TAT,4 not only depends on the hypotheses developed by Handley and Benton,18 but also on the capacity of the firm to deliver the service, dependent on firm and human resources features (G1: HR-FF); the features of services they offer (G2: FServ); type of contractual relationships (G3: CRS); and the equipment
features under their charge (G4: CEq) (Figure 1). This paper tries to fill the gap in the current evaluation methods of maintenance service provider performance in healthcare institutions. Specifically, the two objectives of this work are: 1. To determine which variables from variable groups G , G , G , and G have a 1 2 3 4 significant influence on the TAT indicator. To build a Cox proportional hazard model to determine quantitatively which of the independent variables in the groups G1, G2, G3, and G4 have a significant influence on the increase or decrease in the probability of higher or lower values of the TAT variable. This study contributes to the clinical engineering field in several fundamental ways. First, the results have the potential to substantially enhance the strategic evaluation processes for maintenance outsourcing in the healthcare industry. Although the variables in groups G1, G2, G3, and G4 (see Methods) for completing an adequate characterization of maintenance service providers were recommended by ECRI,6 there is no current consensus as to which- and to what extent-these variables influence performance of maintenance service provid- ers. Therefore, strategic evaluation processes are difficult to implement because managers do not know which variables to include, nor how to weigh the influence of the variables to make decisions. Second, contractual completeness of outsourcing in the healthcare industry also will benefit. Once the impact of the variables on the TAT indicator is known, medical engineering departments can write better, more detailed contracts, reducing the risks of contract failure, and thus cutting costs and reducing the risks to the downtime of a healthcare institution’s medical devices. Third, this study will be valuable for healthcare institutions in developing coun- tries, where contracting maintenance services often is inevitable because hospitals have fewer properly trained employees on staff, and lack material resources to handle these functions on their own. Additionally, this study creates a methodol- ogy for monitoring and evaluating the performance of maintenance service providers using statistical analysis, helping managers make better decisions about which variables to include in future strategic evaluation and contract completion processes. To the knowledge of the authors, the problem of quantitatively determining the independent variables in groups G1, G2, G3, and G4 with a significant influence on the values of the TAT variable have not been empirically explored in the existing health- care industry literature. Contextual Issues Regarding the Structure of the Colombian Healthcare System and the Maintenance Modalities of Medical Devices Healthcare services in Colombia are deliv- ered through a complex system which revolves around the General System for Social Security in Healthcare (SGSSS) which consists of two main components, run by the federal government: the Contribution System (RC) and the Subsidy System (RS). The RS affiliates those who are unable to pay the monthly healthcare payroll deduction (such as those earning salaries below the legal mini- mum wage of U.S. $249 per month), while the RC affiliates formally employed workers capable of making this contribution, typically between 4-8% of their monthly wage. In 2010, the RC and RS provided coverage to 39.7% and 51.4% of the total population, respectively. For the delivery of healthcare services, the system rests upon two fundamental pillars: (1) the insurance providers, which may be either public or private entities which insure the population and act as intermediaries between the State and medical service providers. These are called healthcare service promoters, known by the Spanish acronym, EPS. (2) The healthcare service providers (known by the Spanish acronym, IPS) include the hospitals, clinics, and laboratories that provide direct healthcare services to users, who pay directly for these services in order to obtain higher quality care than may be available under the SGSSS.20 According to a report by the Ministry of Social Protection, total healthcare expendi- tures as a percentage of GDP average 8.5% during the period between 1993 and 2003. On the other hand, during the same period, the percentage of healthcare expendi- tures corresponding directly
to medical services was 66.2%, while 17% went to administrative costs, 8% corresponded to healthcare investments, and 8.8% to other costs.20 According to the country’s Special Registry of Health Service Providers (REPSS), there were a total of 46,358 health- care providers (IPS and EPS) in 2010. Of these, 10,390 were IPS (9,277 private and 1,113 public), 34,933 were independent professional medical specialists, 341 were special medical transportation companies (ambulances), and 694 corresponded to other medical services. In total, this represents a capacity of approximately 68,000 hospital beds, or approximately 1.5 beds per 1,000 inhabitants.20 In terms of human resources, according to the Center for Development Projects at the Universidad Javeriana of Colombia (CENDEX), in 2010 there were approximately 226,600 professionals working in the Colombian healthcare sector, of which 77,000 were doctors, corresponding to 1.7 doc- tors per 1,000 inhabitants. Specifically relating to the specialty of biomedical engineering, in 2011 there were a total of 1,500 engineers and technicians working in the field.21 At a rate of 0.033 per 1,000 inhabitants, that figure is evidence that the human resources in this field are insufficient for the needs of the country. With respect to the maintenance of medical devices in Colombia, there have been three traditional methods for providing equipment maintenance service, including: in-house service by the clinical or biomedical department, the original equipment manu- facturer (OEM), and third party (TP) or independent service organizations (ISOs).21 Obviously, outsourced maintenance services are provided by the OEM and TP, which sometimes share service tasks with a hospi- tal’s in-house service department. Maintenance service by the OEM may be on-demand or under contract-during or after warranty-and requires overseeing the quality of the maintenance service performed. A TP is used when the OEM delegates its maintenance service to one. A TP has the same requirements as those of the OEM, with respect to monitoring and quality measure- ment of maintenance service performance. Providing a full characterization of mainte- nance service provider and the maintenance modalities (i.e., outsourced or in-house) in the Colombian context is out of the scope of this paper. Still, some scholars have reported that this market is characterized by, (1) a high level of maintenance outsourcing services in hospitals, in some cases more than 62.23% of the total medical inventory; (2) the mainte- nance service providers are companies that can be catagorized as experienced (i.e., with an average value of 25 years of experience in the industry) and small (i.e., human resources total of three personnel, including technicians and engineers); (3) with poor infrastructure to provide maintenance services. For example, Cruz et. al22 found that 15.38% of maintenance service providers had no equipment replacement stock held in the country and 11.50% did not offer online assistance. In addition, the same study found poor maintenance service provider perfor- mance, characterized by high turnaround time values for medical devices, with an extreme TAT value of 101 days; and an average value of 9.79 days. In Colombia, hospital administrators face many challenges when deciding whether to outsource maintenance services. For exam- ple, when hospitals purchase highly complex equipment and the OEM refuses to allow other maintenance organizations (i.e., ISO) access to products such as online diagnostic programs and/or very specific spare parts, hospitals become locked into maintenance contracts with the OEM to gain access to such services, driving costs above what they would be in a competitive environment. Additionally, TP maintenance providers often lack the ability to invest in such idiosyncratic assets due to the high costs involved in using highly specialized parts and the additional cost of keeping parts in storage. Parts are thus ordered on an on- demand basis from an external supplier, such as the OEM, resulting in longer equipment turnaround time. If the OEM does not have a formal policy of supporting other maintenance companies, it may view other companies as competitors with respect to its own equipment mainte- nance business and thus delay or block the sale of specific spare parts. Research Methods This study was conducted in a public hospi- tal, of “high-level complexity,” according to the Colombian Ministry of Health hospital classification, with three full-time equivalent biomedical technicians in its clinical engi- neering department. The hospital has an average of 245 licensed beds, with a total of 1,050 medical devices in its
inventory. The total inventory value (in Colombian pesos) is about $24,101,821,107 (i.e., approximately U.S. $12,050,910), with an average of service cost versus acquisition cost ratio of 8.7%.19 For the equipment inventory, the average value of the equipment’s usage time versus useful life versus usage time ratio was 0.86. The authors of this paper followed the methodology proposed by Miguel et. al.20 First, a study characterizing the hospital’s inventory was conducted. The main goals were to determine the state of the equipment inventory and to determine which medical devices were under outsourced maintenance service. Equipment variables for inventory characterization were monitored in nine pilot areas5 in the hospital under study. One hundred percent of the devices in the pilot areas were included in the data sample (N= 264). For the purposes of this study, the most important variables are the equipment level of obsolescence (Obsolec), calculated as the ratio of equipment use time, in years (UT) to useful life, in years (UL). Particularly, the UT over UL ratio was operationalized as follows: If the UT/UL ratio is lower than one (UT/ UL<1), the equipment is not obsolete. If the ratio is greater than one (UT/UL>1), the equipment is obsolete because it has passed what the OEM considers to be its useful life. We coded technological obsolescence as “NO” if the value of the UT/UL ratio was less than one, while obsolete equipment with UT/ UL ratios of greater than one were coded as “YES”. This transformation from a ratio to binary scale for this variable has proven feasible in many applications to measure the obsolescence of medical devices.22 The technical complexity of equipment was measured in categories of high, medium, and low complexity (Complex). Finally, the equipment types (EqTypes) included were Diagnostics, Treatment, Monitoring, Support, and Laboratory.23 Next, a survey was designed and conducted to characterize maintenance service provid- ers (n=19). A total of 18 variables were studied, including the following: contract duration, in years (ConDur); total quantity of equipment included in the contract (NEquip); maintenance type (MaintType); whether the contract is a warranty maintenance contract (ContRel); whether the maintenance service provider has replacement parts in the country where the service is offered (RepParCount); whether the contract includes replacements parts (REParts); the number of annual visits stipulated in the contract (NvisitYear); equipment types involved in the maintenance service contract (EqTypes); number of engineers and technicians working on the contract (TotalHumResContract); experience of the company’s human resources, in years (ExpPersonalYear); distance of the service provider from the hospital, in kilometers (HospDist); quantity of contracts managed by the service provider(TotNumContracts); experience of the company in the industry, in years (ExpCompany); whether remote diagnostic for both maintenance and correc- tive services are offered (ServLine); and whether training is provided to equipment users, operators, and technicians (UserTrain- ing and TechTraining); and finally, the technical complexity (Complex) and level of obsolescence (Obsolec) of equipment involved in every maintenance transaction. All independent variables for both inventory and maintenance service provider characteri- zation were then classified into groups. Group 1 (G : HR-FF) included variables 1 measuring service provider and human resource features; Group 2 included the service features they offer (G : FServ); Group 3 included variables measuring the type of contractual relationships (G : CRS); and last, Group 4 measured the equipment features under their charge (G : CEq) (for more details see column 2 of Table 1). Next, the research team monitored each service provider for the turnaround time (TAT) variable (i.e., the dependent variable), using the work orders of every corrective and scheduled maintenance task the service provider performed over a six-month period (N=1,025). Normally TAT is defined as the time from service request until the equip- ment is back up and running. As both response time and downtime of maintenance service provider is included in TAT, we decided to use TAT as dependent variable instead of the time that equipment is unavail- able due to repair or preventive maintenance, i.e. downtime. The authors of this research believe that TAT is a more comprehensive indicator than others (i.e. downtime, in hours), because it directly relates to the availability of medical devices (i.e. lower values of medical device TAT means lower values of availability6) making it an appropri- ate indicator of maintenance performance. Obviously, the timeframe for TAT calculation differs if the work order is preventive or corrective.24
Next, a descriptive statistical analysis was conducted for all variables. Each variable from groups G1, G2, G3 and G4 was catego- rized into dummy (YES=1 or NO=0) or categorical variables (see column 3 of Table 1). This categorization allowed us to conduct statistical tests8 between the variable catego- ries in groups G1, G2, G3 and G4 and the TAT values for each category (see column 5, i.e. Log Rank Test of Table 1). Where these tests produced significant results (i.e., p value <0.05), we concluded the variables from groups G1, G2, G3 and G4 have influence on the TAT of maintenance service providers. As shown in Table 1, most tests for these variables produced significant results. Thus, the next step was to quantify the relationship between variables in groups G1, G2, G3 and G4 and TAT. To do that, a Cox proportional hazard model was built. In this model, variables of groups G1, G2, G3 and G4 are called co- variables. The methodology fol- lowed to build the model was proposed by Hosmer.25 The elimination or inclusion of covariables in the Cox model is a combina- tion of expertise, with support from contingence tables to eliminate problematic multicollinearity, and the patience of the data analysts. Finally, an assessment of the Cox model's adequacy was conducted (see results for more details). Results Table 1 shows the results of the statistical tests, as a necessary step before building the Cox model, between categories of independ- ent variables of groups G1, G2, G3, and G4, and TAT. Table 2 gives the estimated coefficients for the Cox proportional hazards model containing significant variables (p <0.05). The statistical tests between the categories of independent variables in groups G1, G2, G3, and G4, and TAT showed in Table 1, provide highly significant values at p <0.05, and in many cases at p <0.01. In addition, the medians of TAT for each co-variable category calculated by Kaplan-Meier method using the Log Rank test exhibit different values and provide highly significant values at p <0.05, and in most cases at p <0.01. Therefore, we found statistically significant evidence (p-values <0.05) to support that 17 of 18 of our variables studied have an impact on mainte- nance performance of service providers, i.e., TAT (Table 1). The Cox model found that the subset of significant variables that determine the quantitative relationship in terms of increase or decrease in risk for higher or lower values of TAT in function of variables in groups G1, G2, G3, and G4 were: whether the mainte- nance service providers have replacements parts in the country the service is offered (RepParCount (G )); distance of the service 1 provider from the hospital, in kilometers (HospDist (G )); the number of annual visits 1 stipulated in the contract, including both preventive visits (NvisitYear (G )); whether training is provided to users (UserTraining (G )); maintenance type (MaintType (G )); 23 and technical complexity of equipment (Complex (G )) (see Table 2 for more details). 4 Discussion and Managerial Implications The managerial implications of this research are intended to determine which variables should be included in the evaluation, selection, and contract formulation processes of purchasers of outsourced maintenance services in the field of medical device mainte- nance contracts. This in turn should help to obtain better contractual completeness results. It is true that the "contract alone is not sufficient to align objectives and mitigate external sourcing risks"3 and to obtain better performance of maintenance service provid- ers. However, in developing countries, where a lack of standardized contracting proce- dures, methodologies, and variables to measure the performance of maintenance service providers is common, the determina- tion of the variables that impact performance and the respective inclusion of penalties in the contract are very important issues that deserve to be studied. From a managerial perspective, our results lead to a number of implications for the selection and negotiation processes with medical device maintenance service provid- ers. Some of the most important are: 1. We found that the higher the geographical distance between the maintenance service provider, the higher the TAT values. Our suggestion here is, whenever possible, ensure that the maintenance service provider has the technical capability to provide the service using either a diagnos- tic remote service or through the adoption of Help Desk concept service. During the negotiation process, make sure that maintenance service providers have
invested in ancillary telecommunication infrastructure to incorporate and extend the maintenance support of medical devices at distances geographically sepa- rate from maintenance service providers. 2. We also found higher TAT values when the maintenance service provider did not have equipment parts in the same country in which maintenance service was provided. Our suggestions here are: (a) negotiate at least a 10-year post-warranty provision of critical parts with the equipment vendor at the time of purchase, and establish channels with the OEM for subsequent purchases of spare parts; (b) whenever possible, for both clinical engineering departments and government healthcare systems, create a specific internal depart- ment (e.g., National Physical Asset Management Bodies) responsible for the supply of medical equipment spare parts, especially for low-income countries; (c) during the selection process, identify the best maintenance service providers, in terms of efficiency, speed, and quality for spare parts delivery. 3. We found that TAT is lower if the mainte- nance service provider includes some specific repair parts in the contract agreement. The advice here is, whenever possible during the negotiation phase, ensure the inclusion of necessary terms and conditions in contracts with mainte- nance service providers in order to guarantee the inclusion in the contract of parts crucial to the maintenance tasks. Some maintenance service providers abuse their competitive advantage because they are the exclusive providers of very specific spare parts, leading to low perfor- mance. However, such a practice damages their reputation and may result in hospital managers switching to a competitor. 4. Our research shows that if maintenance service providers use remote diagnostic tools during maintenance tasks the TAT is lower. Our suggestion here is that when buying high technology equipment, hospitals should negotiate the purchase of software diagnostic tools directly with the OEM at the time of equipment purchase whenever possible. By negotiating the purchase of these auxiliary tools at the time of equipment purchase, hospitals may increase their leverage over the OEM, which otherwise might be unlikely to relinquish exclusive control over such software. 5. We found the higher the number of preventive maintenance visits per year, the higher the TAT. Therefore, managers of clinical engineering departments need to control preventive maintenance frequency in order to optimize equipment availability. While some maintenance service providers offer unlimited preventive maintenance visits per year as a competitive advantage, high preventive maintenance frequency actually reduces equipment availability, increasing the TAT. Therefore, it is impor- tant for managers of clinical engineering departments to balance the need for preven- tive maintenance to keep equipment from breaking down, with the risk that excessive preventive maintenance needlessly increases equipment TAT. We recommend following the maintenance frequency suggested by the manufacturer of the equipment. Only in cases where there is sufficient statistical evidence for increasing maintenance frequency should mainte- nance frequency be changed. However, before doing so, the manager of the clinical engineering department should consider multiple factors (e.g., the regulatory environment, the physical environment, the reliability of the equipment, how much wear the equipment receives during normal use, etc.) The analysis of all these factors that lead to the modification to the mainte- nance frequency should be presented to a multidisciplinary safety committee or hospital quality management commission to make the final decision. 6. Our study suggests that for some medical devices, high preventive maintenance frequency (more than six visits per year) may be necessary. Therefore, it is recom- mended whenever possible to take a variety of approaches to reduce TAT, including: (a) schedule all maintenance tasks of equip- ment located at the same clinical location (e.g. emergency care unit, operating rooms, or clinical laboratory) at the same time, or (b) to schedule all the maintenance tasks for all equipment of a given type (e.g. defibrilla- tors, electrocardiographs) at the same time. Equipment located in the same areas generally have the same level of complexity and risk; thus, these strategies should not be difficult to implement. 7. We found that if maintenance service providers do not provide training to users and technicians, there is a negative impact on TAT. While this result seems obvious, many low-income countries face problems with
medical device operation and mainte- nance due to a lack of training. Our suggestions follow: Make sure that maintenance service providers have proper continuing education programs for both users and biomedical technicians. User training programs should focus on proper operation of medical devices, daily mainte- nance, and fault reporting symptoms of technical systems. As medical device users are on the frontline of patient care, they play a fundamental role in identifying and reducing potential medical device prob- lems that could lead to patient injury. On the other hand, technician training programs should be focused on identifica- tion of the training strategies for every type of technician profile, whether oriented or problem solving. Whenever possible, provide continu- ing training in factories in which the equipment has been designed and assem- bled. The inclusion of these facilities as an “aggregate value” to service can increase service quality reputation. During the service provider selection process, the quality of a provider’s training packages should be taken into account in the analysis. (4) Be aware of proper inclusion of clauses in the contract that ensure training to both users and techni- cians. Maintenance service providers that do not offer this possibility should be eliminated from the selection process. 8. The results of this research showed that the higher the contract duration, the higher the TAT. We strongly suggest making one-year base arrangements in order to monitor the maintenance service provider’s performance, especially in cases where the healthcare institution lacks basic contracting skills, or does not have the possibility to completely verify the techni- cal capability of the maintenance service providers either at the time of contract signing or during contract running. Limitations and Opportunities For Future Research This study can be improved in many ways. The data sample hospitals and maintenance service providers should be increased, while at the same time new covariables should be included in future studies. Increasing the number of hospitals and maintenance service providers in the data sample would provide more generalized results in the effects of covariables in groups G1, G2, G3, and G4 in the TAT. The inclusion of new co-variables in the Cox model, such as the type of healthcare institution (public or private), the contract cost, the priority ranking (high, medium or low), the medical service type (imaging, surgery, emergency, etc.), the weather conditions, the road infrastructure, whether penalties in the contract are established, and the time that the healthcare institution takes for releasing pay orders deserve to be studied for their potential impact on TAT. Conclusions It has been pointed out that outsourcing and outsourcing performance alters the risk profile of the supply chain.3 The results obtained in this study offer strong empirical evidence for this finding. This is the main contribution that this paper makes. From this research, the authors can conclude that: 1. The capacity of the firm to render its services (firm and human resources features) (G : HR-FF); the features of services they offer (G : FServ); type of contractual relationships (G : CRS); and 3 finally, the equipment features under their charge (G : CEq) have an impact on a maintenance service provider’s perfor- mance (TAT, alters the risk profile of supply chain). This is supported by the measure of the R2 = 0.57, with a value of R = 0.75 of p,e p,e the Cox model built. Thus, it can be said that covariables account for 57% of the variation in the TAT variable, with moderate high positive correlation between covari- ables (independents) and the dependent variable (TAT) (i.e. the R2 = 0.57). p,e The Cox model built allowed the research team to find the most significant variables that affect the maintenance service providers’ performance (TAT). These are the distance of the service provider from the hospital, in kilometers (Km) (HospDist (G )); whether the maintenance service 1 provider has replacement parts in the country the service is offered (RepParCount (G )); whether training is provided to equipment users (UserTraining (G )); mainte- nance type (MaintType (G )); technical complexity of equipment (Complex (G )); and the number of annual 4 preventive maintenance visits stipulated in the contract (NvisitYear (G )). n Acknowledgment
We would like to thank COLCIENCIAS for the resources provided in Grant Announcement 459/08, which financed this study. Thanks to Sandra Usaquen Perilla and Nidia Nelly Vanegas Pab?n who helped in the data collection phase of our research. Thanks also to University Hospital La Samaritana for its support and collaboration in completing this study. Finally, thanks to Milciades Iba?ez Pinilla for his advice on the statistical model selection in the beginning stages of this project. Sidebar The results obtained from previous studies indicate that the evaluation of outsourcing performance merits deeper evaluation, as no statistical evidence was found to support the hypotheses that contractual completeness and strategic evaluation have positive effects on outsourcing performance. This study creates a methodology for monitoring and evaluating the performance of maintenance service providers using statistical analysis, helping managers make better decisions about which variables to include in future strategic evaluation and contract completion processes. References References 1. Tarakci H, Tang K and Teyarachakul S. Learning Effects on Maintenance Outsourcing. European Journal of Operational Research. 2009;192:138-150. 2. Greene J. How Much Privatization? A Research Note Examining the Use of Privatization by Cities in 1982 and 1992. Policy Studies Journal. 1996;24(4):632-640. 3. Benton J. And Menzel J. Contracting and Franchising: County Services in Florida. Urban Affairs Quarterly. 1992;27:436-456. 4. Carver R. Examining the Premises of Contracting Outsourcing. Public Productivity and Management Review. 1998;8:27-40. 5. Hirsch W. Privatizing Government Services: An Economic Analysis of Contracting Out by Local Governments. 1991. Los Angeles: University of California. 6. ECRI. Types of Services: Their Advantages and Disadvantages. Health Technology. 1989;3(4):9-20. 7. Jensen D. Contract Worker Services: An Inside View. Aviation Management. 2006. Available at: www.aviationtoday.com/am/ categories/bga/Contract-Worker-Services-An-Inside-View_6139. html#.US99- 2e3XEM. Accessed Feb. 27, 2013. 8. Landis K, Mishra S and Porrello K. Calling a Change in the Outsourcing Market: The Realities for the World’s Largest Organizations. 2005. Deloitte Consulting Report. 9. Doig S, Ritter R, Speckhals K, and Woolson D. Has Outsourcing Gone Too Far? McKinsey Quarterly. 2001:24-37. 10. Robinson P, Lowes P, Loughran C, Moller P, Shields G, and Klein E. Why Settle for Less? Outsourcing Report. 2008. Deloitte Consulting Report. 11. Murthy D and Asgharizadeh E. Optimal Decision Making in a Maintenance Service Operation. European Journal of Operational Research. 1999;116:259-273. 12. Asgharizadeh E and Murthy DNP. Service Contracts: A Stochastic Model. Mathematical and Computer Modelling. 2000;(31):11-20. 13. Plambeck E. And Zenios S. Performance-Based Incentives in a Dynamic Principal-Agent Model. Manufacturing and Service Operations Management. 2000;2:240-263. 14. Tarakci H, Tang K, Moskowitz H, and Plante R. Incentive Maintenance Outsourcing Contracts for Channel Coordination and Improvement. IIE Transactions. 2006a;38:671-684. 15. Tarakci H, Tang K, Moskowitz H, and Plante R. Maintenance Outsourcing of a Multiprocess Manufacturing Dystem with Multiple Contractors. IIE Transactions. 2006b; 38:67-78.. 16. Wang K. and Lee W. Learning curve analysis in total productive maintenance. The International Journal of Management Science. 2001;29:491-499.
17. Trevor L. And Potoski M. Managing Contract Performance: A Transaction Costs Approach. Journal of Policy Analysis and Management. 2003;22(2): 275-297. 18. Handley SH and Benton WC. Unlocking the Business Outsourcing Model. Journal of Operations Management. 2009;27(5): 344-361. 19. Cohen T. Benchmark Indicators for Medical Equipment Repair and Maintenance. BI&T. 1995; 29(4): 308- 320. 20. Guerrero R, Gallego AI, Becerril-Montekio V, and V?squez J. Sistema de Salud de Colombia. Salud P?blica de M?xico. 2011;53(2): 144-155. 21. Rios-Rincon AM, Miguel CA, Rodriguez CHLE, and Chaparro J. La Ingenier?a Biom?dica en Colombia: Una Perspectiva desde la formaci?n del Pregrado. Revista Ingenier?a Biom?dica. 2010; 4(7):23-43. 22. Cruz AM, Perilla S, and Pab?n N. Clustering Techniques: Measuring the Performance of Contract Service Providers. IEEE Eng Med Biol Mag. 2010;29(2):119-26. 23. Invima. Decreto 4725 de 2005. Invima, Available by password at: www.minproteccionsocial.gov.co/VBeContent/library/documents/ DocNewsNo15472DocumentNo2802.PDF.Accessed Feb. 27, 2013. 24. Cruz AM, Rodr?guez D, S?nchez V, Pozo Pu?ales ET, and Vergara Perez I. Measured Effects of User and Clinical Engineer Training Using a Queuing Model. BI&T. 2003;37(6):405-421. 25. Hosmer WH. Applied Survival Analysis Regression Modeling of Time-to-Event Data. 2nd Edition. Wiley Series in Probability and Statistics. New Jersey. 2008. AuthorAffiliation About the Authors Antonio Miguel Cruz, PhD, is a nuclear engineer with the School of Medicine and Health Sciences at the Universidad del Rosario in Bogot?, Colombia. E-mail: antonio.miguel@urosario.edu.co Adriana Maria Rios Rincon, MSc, is an occupational therapist with the school. E-mail: adriana.rios@ urosario.edu.co Gregory L. Haugan, BA, is a research assistant with the school. E-mail: haugangl@ gmail.com MeSH: Equipment & Supplies, Hospital, Hospital Departments, Humans, Models, Statistical, Program Evaluation, Biomedical Engineering — organization & administration (major), Biomedical Engineering — standards (major), Maintenance — methods (major), Maintenance — standards (major), Outsourced Services (major) Publication title: Biomedical Instrumentation & Technology Volume: 47 Issue: 6 Pages: 524-35 Number of pages: 12 Publication year: 2013 Publication date: Nov/Dec 2013 Year: 2013 Section: Columns and Departments Publisher: Allen Press Publishing Services Place of publication: Philadelphia
Publication subject: Medical Sciences ISSN: 08998205 Source type: Scholarly Journals Language of publication: English Document type: Feature, Journal Article Document feature: Diagrams Tables References Accession number: 24328978 ProQuest document ID: 1471052019 Document URL: http://search.proquest.com.ezproxy.libproxy.db.erau.edu/docview/1471052019?accountid=27203 Copyright: Copyright Allen Press Publishing Services Nov/Dec 2013 Last updated: 2014-02-19 Database: ProQuest Central,ProQuest Advanced Technologies & Aerospace Collection
_______________________________________________________________ Contact ProQuest Copyright ? 2016 ProQuest LLC. All rights reserved. – Terms and Conditions

Leave a Reply

Your email address will not be published. Required fields are marked *