integrated logistic support and equipment availability in ...integrated logistic support the concept...

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G S K DharmaratneA K L Jayawardana

M W Gunatunga

Abstract

This study examines the perceived integrated logistic support and the equipment availability ofseven equipment categories in four selected base hospitals in Sri Lanka. This includes measurementof actual downtime of eighty five pieces of medical equipment prospectively by direct observationfor a period of sixty consecutive days. The logistic support considerations were: preventivemaintenance support, corrective maintenance support, supply support, facility support, staffavailability and training and skill support. These were assessed in terms of eighteen constructs asperceived by the operator staff.

The results indicate that 57% mean operational availability and technical faults accounted for77% of the downtime. Low practices of periodic inspections, service agreement support andmaintenance planning were noticed. Speedy fault reporting was observed but fault inspectionswere relatively late. Lack of consumables and lack of facilities resulted in 7% downtime each.Twenty five pieces of equipment had zero availability throughout the study period. Furthermore,corrective maintenance support (r=0.66) and preventive maintenance support (r=0.44) werepositively correlated with operational availability and such associations were statisticallysignificant. The study suggests that health managers should focus more on preventive andcorrective maintenance and take measures to improve equipment availability.

Key words: Equipment availability, Integrated logistic support, Operational availability,Downtime, Preventive maintenance support, Corrective maintenance support, Supply support,Facility support, Staff availability and Training and Skill support,

Integrated Logistic Support and EquipmentAvailability in Government Hospitals of aDeveloping Country

Dr G S K Dharmaratne, holds an MBBS, M.Sc., and an MD (Medical Administration). Dr. Dharmaratnepresently functions as Medical Superintendent at the District General Hospital, GampahaDr M W Gunathunga possesses an MBBS, M.Sc., and an MD (Medical Administration) in CommunityMedicine. Currently Dr. Gunathunga is a Senior Lecturer, at the Department of Community Medicine, Facultyof Medicine, University of Colombo.Dr. A. K. L. Jayawardana is presently an Associate Lecturer at the school of Managemen, Marketing andInternational Business, Australian National University, and Senior Consultant, Postgraduate Institute ofManagement (PIM), Colombo, Sri Lanka.

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1. Introduction

The pace of technological innovation has accelerated in the last few decades especially in thefield of medicine and delivery of health services (Bronzino,1995). This is true even of developingcountries as they are under pressure to acquire novel health care technologies under theimpact of forces created externally from technology providers and donor agencies, andinternally from rising health care expectations of their populations (Heimann and Poluta,1997). Moreover, this trend in technolgy driven societies and health care organizations willpersist and be continuously on the rise and hence, the availability and proper utilization ofmedical equipment are considered vital for efficient and cost effective health care deliveryat all levels of the health sysem (Lathwal and Banerjee, 2001).

Medical equipment brings along with its benefits, associated problems (Pardeshi, 2005) andmany developing countries are characterized by poor management of health care equipment(Al-Fadel and Al-Akaidi 1996) and do not have the resources to ensure proper health caretechnology management (Poluta, 2002). In a study of twelve university affilated tertiary carehospitals in China, Peabody and Schmitt (1992) suggest that an average of 41% of equipmentis working properly. WHO estimates that less than half of all medical equipment is usable(Issakov, 1994). In many countries, there are severe shortages of adequately trained,experienced technical personnel in the health care technical service. Without the correctlevel of technical staff, hospitals cannot benefit from their investments in medical equipment.

Purpose and Justification of the study

There are not many studies that have focused on the utilization and availability of medicalequipment, and several scholars (Cook, 1997; Lam, 2006) have emphasized the importanceof mapping medical equipment downtime. This study intends to identify the downtime ofselected pieces of medical equipment in Sri Lanka for several reasons. First, healthcare serviceinterruptions are not uncommon phenomena in developing countries (WHO, 1996), andfrequent breakdowns, delays in repairs, lack of consumables and inadequacy of staff are oftenhighlighted in the mass media. However, such claims need to be tested empirically as theseshortcomings hinder patient care. Second, medical equipment is a sine qua non in health careservice delivery in any healthcare setting, and forms a considerable part of healthcareexpenditure. For example, in 2006, Rs.1.5 billion was allocated for purchasing bio - medicalequipment for Central Ministry Hospitals in Sri Lanka. This amount exceeds 3% of the totalallocation of the Ministry of Health (Annual Estimate of Treasury, 2006). In order to ensure thetechnical efficiency of such resources, an assessment of equipment availability is imperative.This study intends to understand operator perception of the factors that influence equipmentavailability. Thus this study will give a picture of the lapses occurring in health care institutionsso that health managers can take necessary remedial measures.

It is intended in this study to determine the degree of availability of medical equipment andthe perceived integrated logistic support and the extent to which the varying levels of supportrequirements affect equipment availability.

Sri Lankan Journal of ManagementVolume 15, Nos. 2 , 3 & 4

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Litraure Revivew

Equipment Availability

“Equipment availabilty” is cited as the key determinant of “overall equipment effectiveness”.(Blanchard, 1998) takes a holistic view of the impact of the equipment function onorganizational performance in terms of being available when needed (equipment availability),running at the ideal rate (performance efficiency), and producing first class quality output(rate of quality). “Equipment availability” is classified by many scholars in various ways.However, before discussing these classifications, it is important to differentiate between theconcept of “equipment availability” and “utilization of equipment” as both of these conceptshave been used interchangebly to denote performance of equipment (Peabody, 1992;Pardeshi, 2005). “Equipment availability” is generally defined as the ratio of available hours totarget hours of operation of equipment and indicates ‘readiness for use’. Hence, it shows theeffectiveness of maintenance and logistic support of the system in which equipment operates( Lam, 2006).

In contrast, “utilization” of equipment is defined as the ratio of operating hours to availablehours (Sharma, 2003) or the percentage of plant operating time during which equipment is inproduction (Katkoori, 2007). Hence, it denotes capacity utilization for a section or plant andindicates the performance of the production department (Sharma, 2003). Hence, “availability”is a pre-requisite for utilization and these two concepts are being used to denote two differentaspects of equipment performance (Vorster, 2007).

Barlow and Proschan (1975) define “availability” of a repairable system as “the probability thatan item of equipment is operating at a specified time”. Mathematically, Sharma (2003) expressesit as “(Available hours - downtime) x 100/Available hours” and Blanchard (2004) gives aqualitative definition of availability “as a percentage measure of the degree to which equipmentis in an operable and commitable state at the start of a mission, when the mission is called forat unknown random time”.

Lam (2006) suggests that equipment availability is determined by “reliability” and“maintainability” of the equipment. Reliability is shown as a characteristic of the design ofequipment which results in the durability of the item. It is the capability of equipment to workwell and work whenever called upon to do the job for which it was designed (Sharma, 2003).Maintainability is defined as the probability that an item of equipment will be restored to acertain specific condition within a given period, when maintenance is done according to aprescribed proceedure and resources (Sharma, 2003; Lam, 2006). It is argued that if oneconsiders both relability (probability that the item will not fail) and maintainability (probabilitythat an item is successfully restored after failure), then an additional metric is needed for theprobability that the component is operational at a given time. This metric is “availability” and itis described as a performance criterion for repairable equipment that accounts for bothreliability and maintainability of the equipment ( Lam, 2006).

Integrated Logistic Support and EquipmentAvailability in Government Hospitals

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Classifications of Equipment Availability

Availability measures are classified by either the time interval of interest or the mechanismsfor the equipment downtime if the time interval is the primary concern. Barlow and Proschan(1975); Lie, Hwang and Tilman (1977) and Nachalas (1998) suggest instantaneous (point),average uptime (mean) and steady state availability. Accordingly, (Keeter, 2002) suggests“instantanous availability” as the probability of an item of equipment being operational at anyrandom time , and “mean availability” as the mean of value of instantaneous availabilityfunction over a period of time and “steady availability as the limit of the instantaneous availabilityfunction as the time approches infinity.

If the mechanisms for downtime is the primary concern, Lie, Hwang and Tilman, 1977; andBlanchard, 1998 suggest inherent, acheived and operational availability. Accordingly, “inherentavailability” is described as a steady state of availability which is determined by only thecorrective maintenance downtime. Lam (2006) has shown that it can be calculated by usingreliability and maintainability indicators; mean time between faliures (MTBF) and mean timetaken for repair (MTTR) as it is only concerned with corrective maintenance downtime.Achieved availability is determined by both preventive and corective downtimes (Katukoori,2007) assuming that resources are hundred percent available. Operational availability isdescribed as a measure of the average availability over a period of time and it includes allexperienced sources of downtime. It is the probability that an item will operate satisfactorilyat a given point in time when used in an actual or realistic operating and suppport environment(Lam, 2006) and reflects plant maintenance resource levels and and organizationaleffectiveness. In contrast to other models of availability, operational availability is essentiallybased on actual events that happened to the system; hence, the customer actually experiencesit.

Integrated Logistic Support

The concept of integrated logistic support (ILS) was formerly developed in the mid-1960sand at that time it was defined as “a composite of all support considerations necessary toassure effective and economical support of a system or equipment at all levels of maintenancefor its programmed life cycle” (ILSP Guide,1967 cited in Blanchard, 2004). Since then,intergrated logistic support has been used more and more by organizations to plan how theproducts that they developed will be supported over their life cycle (Legg and Paul 1980).

The principles and concepts of ILS have been developed further and its definition expandedto constitute a unified management of the technical logistics elements that plan and developthe support requirements for a system (ILSP Guide, 1994 cited in Blanchard 2004) anddefined as the management process which facilitates development and integration of theten individual support elements to specify, design, develop, acquire, test, field, and supportsystems.

The ten logistic elements of ILS are: maintenance planning and support ; supply support;support and test equipment; manpower and personnel; training and training devices; technicaldata; computer resource support; packaging, handling, storage and transportation; facilities;


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and design interface (Blanchard 1998). It has been shown that all elements of ILS must bedeveloped in coordination with the system engineering effort and with each other. However,it has been suggested to have trade offs between elements in order to acquire a system orequipment that is affordable (lowest life cycle cost), operable, supportable, sustainable,transportable, and environmentally sound within the resources available (Blanchard 2004).

Preventive maintenance is described as a core function of clinical enginnering, based on theprinciple of periodic, often precheduled, inspection and service of equipment in respect ofone or more aspects of ongoing performance of medical devices. These include equipmentlongevity, detection of future need for major service or replacement, maintenance for properperformance, prevention of downtime due to failure, reduction of repair costs and preventionof equipment becoming hazardous when in proper operating condition ( Hyman and William,2003). However, it is suggested that a device should be scheduled for periodic inspection ormaintenance only if there is good reason to provide such support (Hertz 1990). Bronzino,(1992) suggests that an appropiate scheduled maintenance frequency has to be decided onin order to ensure longevity, reliabilty, accuracy and safety of the device. Furthermore, Ridgeway(2003) has pointed out that frequent inspections may degrade device longevity and may notbe cost effective whereas periodic inspections that are not frequent enough may adverselyaffect the longevity of equipment.

Dunscombe, Roberts and Valiquette, (2000) state the importance of mapping out ofmaintenance schedules for cleaning, repairs and parts replacement. Furthermore, Lee andMie-Yun (2000) show that service level agreements can help to reduce the downtime ofequipment but it is necessary to guarantee the degree to which the equipment is workingand available. Ridgeway (2003) suggests that there is no satisfactory persuasive evidencethat improved reliability of equipment would allow managers to relax on traditional plannedmaintenance practices without compromising the patients’ safety. Conversely, Hyman andWilliam (2003) argues that preventive maintenance does not, and cannot, prevent all types ofequipment malfunction as many failures are effectively “random,” or at least unpredictable intime and undetectable in advance and the value of preventive maintenance should not beover - stated.

Corrective maintenance or “repair” is defined as trouble shooting to isolate the cause of devicemalfunction and then replacement or adjustment of components or subsystems to restorenormal function, safety, performance, and reliabilty (ECRI,1990). Bronzino (1992) states thatcorrective maintenance is carried out in three steps: diagnose of the problem, repair orreplacement of the faulty component, and verification of the repair and it can include any orall of the following steps: localization, isolation, disassembly, interchange, reassembly,alignment and checkout. According to Bronzino (1992), this area can be expanded andvisualized as administrative delay time, technician’s non-response time, logistic delay timeand actual repair time. Various scholars have different views on the computation of downtimeof corrective mantenance (Cook, 1997), and recently, Sharma (2003) emphasizing the processof corrective maintenance states that speedy fault detection, speedy fault diagnosis, speedyrepairs and reduction in waiting time for repair are ways of reducing downtime.


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Supply support is defined as providing the expertise required to support the aspects of supplyrequirements.This encompasses all the management actions, procedures and techniquesused to determine requirements to acquire support items and spare parts, receive items,store, transfer, issue items, etc. This element includes all spares, repair parts, consumables andspecial supplies (Blanchard, 2004).

The facilities logistics element is composed of a variety of activities (Blanchard, 2004). Thisencompasses those management actions, proccedures,and techniques used to ensure thatall required permanent or semi-permanent operating and support facilities are availableconcurrently with system fielding. According to him, facilities management should also havea focus on providing a healthy environment for staff, patients and the community.

In view of manpower and personnel support, a study conducted by the Planning Commissionof India (1999) shows that mismatches between staff and equipment have resulted in suboptimal utilization of equipment. Chitre and et al (2000) have also observed underutilizationof X-ray machines due to non-availability of surgeons in rural hospitals in India. Hymen,William, Cram, and Nicholas (2002) suggest that adequate consideration of human factorsissues are essential when assessing and implementing medical equipment in a clinical setting.They further suggest that patient- user device interface is within the domain of the clinicalengineer and skills of the operator, the environment, and other operational features can havea dramatic impact on the effectiveness of a medical device. Pardeshi (2005) analysedsecondary data from the Auditor General’s report in twelve states of India, and suggests thatfifteen out of forty cases (37%) of the equipment could not be put to use due to unavaialbiltyof qualified staff. This includes non-appointment as well as non-creation of required posts.

Even the best equipment in the world is valueless without a competent operator. As Fennigkoh(1990) points out, it is likely that operators make erratic reports concluding device malfuntion;however, when the equipment is being examined by technicians, no problems are found.Since, these operator error reports cause unneeded expenditure of technician time and costto the hospital, he claims that the clinical engineer should play an active role in eliminatingsuch errors by providing in-service training. However, Peabody and Schmitt (1992) suggestthat 85% of operators in selected Chinese hospitals have not received any kind of training andonly 15% of respondents have been instructed on how to operate the equipment. Sharma(2003) states that most operators have acquired their skills by self-instruction or from otheroperators mostly by trial and error; hence, adequate thought must be given to decide whowill run this equipment and how they will be trained to make maximum use of their capabilities.

Keil (2006) suggests that more patients are harmed by operators lacking knowledge, judgementand skills than are harmed by faulty equipment. He described “technical skill” as the ability tofully understand how an item of equipment works and how the function of that machinerelates to the clinical knowledge and clinical judgment. In a study in a Brazilian public hospital,Florence and Calil (2006) used “Health Care Failure Mode and Effect Analysis” to identify thefailure modes of cardiac defibrillators and found several failure modes such as lack ofappropriate care with the device conservation and the lack of knowledge of the operator inrelation to the correct form of operation.


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Preventive maintenance support

Corrective maintenance support

Supply support

Facility support

Staff Availability

Training and skills support

Equipment Availability

Research Question

The study focused on research question: What factors contribute to equipment availability?

Study Framework

Based on the literature survey, several ILS elements were conceptualized into six supportconsiderations: preventive maintenance support, corrective maintenance support, supplysupport, facility support, staff availability, and training and skill support. The study frameworkis shown in Figure 1.

Figure 1. Study Framework

A higher level of equipment availability is associated with a higher level of each element ofintegrated logistic support: preventive maintenance support, corrective maintenance support,supply support, facility support, staff availability, and training and skill support.

Dependent variable

The concept of equipment availability, according to the formula cited in the literature (Sharma,2003; Lam, 2006) is Uptime-downtime x100/Uptime.

Uptime is the planned hours of equipment operation. Downtime is the length of time an itemof equipment is not operational during the planned or targeted hours of operation (Lam,2006).

Independent variables

Although there are several ILS elements that can influence equipment availability, only someof the key areas of greatest relevance are considered. Two focus group discussions and brain


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storming sessions were held to verify these variables. After the focus group discussions, thevariables not appropriate to the Sri Lankan context were removed, while the variables relevantto the Sri Lankan context were included for the purpose of the study. With the knowledgegained from the literature review and information from the focus group discussions, thefollowing independent variables were identified and defined.

Preventive Maintenance support

Preventive maintenance is defined as periodic proccedures to minimise the risk of failure andto ensure continued proper operation of equipment. Thus, preventive maintenance supportis the degree to which the organizations practise periodic inspections, perceived quality ofservicing, service agreement support and maintenance planning.

Corrective maintenance support

Corrective maintenance is synonymous with repair and consists of the actions taken torestore a failed system to operational status. It includes all actions performed as a result offailure, to restore an item to a specified condition. Corrective maintenance support is definedas the organizational practices of fault reporting, fault inspection, coordination of the repairprocess with the maintenance organization, management support received for the repairprocess, speed of repair process and accuracy of repair.

Supply suport

Supply suport is defined as providing expertise required to support the aspects of supplyrequirments.This encompasses all the management actions, procedures and techniques usedto determine requirements to acquire support items and spare parts, receive items, store,transfer, issue items, ete. It is the degree to which health care organizations ensure theavailability of consumables and the managerial support given for the supply process.

Facility support

Facilities, the logistics element, encompasses a variety of activities: reviewing, evaluatingand/or proposing necessary action to accommodate timely facility planning. Facility support isdefined as the degree to which health care organizations provide adequate space andinfrastructure facilities and adequacy of power supply which are needed for continuousoperation of the equipment.

Staff availabilty

Pertaining to this study, operator staffs include doctors of the dental departments, nurses ofthe intensive and baby care units, medical laboratory technicians of laboratories andradiographers of radiology depatments of the hospitals. Staff availabilty is the degree towhich the health care organizations enure availability of operators for continous operationand operationalized in terms of adequacy of staff and possibility of substitution of staff toperform the required operation.

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Training and skill support

Training and skill support is defined as the degree to which health care organization ensureadequacy of training and adequacy of the skill level acquired by the operator to perform thesheduled operation.

Methodology and the Design

The study was designed to understand the operator perception on selected elements ofintegrated logistic support and the factual evidence about equipment availability over a periodof ztime. It was a search for factors that affect the ‘operational availability’ of equipment in fourBase Hospitals in the Western Province of Sri Lanka: Avissawella, Gampaha, Wathupitiwala andPanadura.

Five departments from each hospital and seven categories of medical equipment were selectedfor the study. These departments were Laboratory, X-ray, Dental departments and MedicalIntensive are and Special Care Baby units. The seven equipment categories were: X- raymachine, X- ray film processor, spectrophotometer, flame photometer, infant incubator, ICUventilator and the Dental unit. The cost, organizational importance and frequency of usagewere the criteria for the selection of the categories of equipment. This equipment could notbe considered as homogenous as they had different ages, different brands and supported bydifferent maintenance organizations. Hence, the total equipment available in each categoryin the selected departments of these hospitals was included in the study. Two pieces ofequipment were irreparable and excluded from the study. The rest of the equipment, whichwas either working or not working but serviceable, was included in the study. There wereeighty five pieces of working and serviceable equipment in the sample.

Data was collected by using three study designs: first, a survey questionnaire of 18 items wasgiven to the operators of the equipment in order to capture the user perception of thesupport variables. Four questions were included to measure preventive maintenance support,six questions to measure corrective maintenance support, two questions to measure supplysupport and two questions were included to measure facility support. The last four questionswere on staff availability and training and skill support. Questions were closed ended, Likerttype with a scale ranging from one to five.

Secondly, an observation checklist was used to measure the actual downtime that occurredduring the planned hours of operation of the equipment. This component of the study wascarried out in these hospitals over a period of sixty consecutive days. Further, several focusgroup discussions were held with the operator staff.

Validity of Data

The relevance of the instruments to the specific areas under investigation was assessed forface validity. Content validity was assessed by examining whether or not all relevant aspectsof maintenance, logistics and operator staff supports were covered. The questionnaire wasanalyzed in the developmental phase by the biomedical engineers in the Department of


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Health for consensual validity. Neutral persons made observations and to prevent intra observerbias, observers were trained adequately. During the pilot study, each observer’s recordingswere tested with those of the others to test the percentage of agreement. The observationswere cross checked with the secondary data available in the complaints registers of thesehospitals and it was found that recorded downtime and responses were accurate.

Data Analysis and Findings

Firstly, frequency distributions of the eighteen sub variables were determined according tothe scale of measurement of the questionnaire: very low, low, neutral, high, and very high,and categorized under the six broad variables of preventive maintenance support, correctivemaintenance support, supply support, facility support, staff availability and training and skillsupport. The Microsoft Excel software package was used for this purpose.

Secondly, the downtime and planned hours of each piece of equipment were calculated inorder to determine the operational availability.

Thirdly, the propositions were tested using statistical methods.

Calculation of Downtime

Downtime of each piece of equipment was observed and summarised daily. This providedthe total downtime during the period of sixty days and was the key determinant of operationalavailability. The observed downtime losses were classified into six main categories for thepurpose of analysis. They were: technical faults, lack of consumables, lack of space/infrastructurefacilities, lack of power supply and cleaning of equipment (planned preventive maintenanceshutdowns).

Calculation of the planned hours of equipment

Planned hours of equipment were calculated according to the length of the shift operation ofthe selected equipment category. Five equipment categories -X- ray machine, X- ray filmprocessor, spectrophotometer, flame photometer, and the Dental unit- had planned operationof six hours per day. The other two categories - infant incubator and ICU ventilator had plannedoperation for 24 hours. This was the basis of calculating the total planned hours of each pieceof equipment during the period of study.

Calculation of Operational Availability

The total downtime and the total planned hours of operation of each piece of equipmentduring the period of sixty days having been identified, operational availability was calculatedby using the following mathematical formula:

Operational Availability = Total planned hours of operation – Total downtime / Total plannedhours of operation

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Basic Characteristics of the sample

Category of equipment

Type of Department

X-ray Machine

Spectrophotometer

Flame photometer

Infant incubator

Ventilator

X-ray processor

Dental unit

Radiology

Laboratory

SCBU

ICU

Dental

n

8

10

8

23

18

6

12

14

18

23

18

12

%

(9.4)

(11.8)

(9.4)

(27.0)

(21.2)

(7.0)

(14.1)

(16.5)

(21.2)

(27.0)

(21.2)

(14.1)

Statistical analysis

The purpose of statistical analysis was to test the propositions of the study and it was conductedusing SPSS software package, 13.0 version. This analysis was based on simple bivariate Pearsonproduct moment correlation. Operational availability of each piece of equipment wascorrelated with each variable of the integrated logistic support. The value of response of eachquestion according to the ratings (1 – 5) of the Likert scale was summed up under eachvariable, and the mean value considered for this purpose.


As shown in Table1, 85 items of medical equipment in five selected departments in each ofthe four Base Hospitals -Wathupitiwala, Gampaha, Panadura, and Avissawella- formed thesample. These departments were Radiology, Laboratory, Special Care Baby Unit (SCBU), MedicalIntensive Care Unit (MICU) and Dental department. The sample comprised seven equipmentcategories: Static X- ray Machine, Spectrophotometer, Flame photometer, Infant Incubator,Ventilator, X-ray film processor and Dental Unit. The highest quantity of equipment (n=23)belonged to the category of Infant Incubator. The category of X-ray film processor representedthe lowest quantity of equipment in the sample. The Special Care Baby Units had the highestquantity of equipment whereas the Dental departments had the lowest quantity ofequipment.xx

Base Hospital Wathupitiwala had the highest amount of equipment (30.6%) and Base HospitalAvissawella had the lowest 20.0%). The sample had wide variations of age ranging from fouryears to 28 years. The highest amount of equipment in the sample belonged to the agecategory of 0 < 2 years. Seventeen pieces of equipment were used for more than ten years.The mean age of equipment was 6.3 years with a standard deviation of 5.4 years.

Table1. Distribution of basic characteristics of the sample


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Type of Hospital

Age in years

Total

BH Watupitiwala

BH Gampaha

BH Panadura

BH Avissawella

0 < 2

2 - 4

4 - 6

6 - 8

8 -10

10 <

26

21

21

17

22

7

11

13

15

17

85

(30.6)

(24.7)

(24.7)

(20.0)

(25.9)

(8.2)

(12.9)

(15.3)

(17.6)

(20.0)

(100)

Variable Level of Measurement Total

Very low Low Neutral High Very highn n n n n n

40(47.1%) 25(29.3%) 06(7.1%) 14(16.5%) 00.0% 85 (100%)

16(18.8%) 12(14.2%) 11(12.9%) 34(40.0%) 12(14.2%) 85 (100%)

49(57.6%) 6(7.1%) 5(5.9%) 12(14.1%) 13(15.3%) 85 (100%)

40(47.1%) 14(16.5) 7(8.2%) 22(25.8 %) 2(2.4%) 85 (100%)

Regularity ofperiodic inspection

Quality of servicing

Service agreementsupport

Maintenanceplanning


Source: Survey Data, n = 85 (100%)

Table 2. Distribution of preventive maintenance support as perceived by operator staff

As shown in Table 2, 40 respondents (47.1%) perceived that periodic inspection of theequipment was very low. Twenty five respondents (29.3%) considered it as low. Only 14respondents (16.5%) considered it as high. The results indicated that the practice of periodicinspections in the sample was low. In contrast, 34 respondents (40%) perceived that thequality of servicing was high. Another 14.2% rated it as very high. Only 16 respondents (18.8%)perceived that the quality of servicing was very low. The results indicated that the majority ofequipment (54.2%) received proper servicing. In view of service agreement support, 49respondents (57.6%) perceived it as very low and another six respondents considered it aslow. It indicated that a significant proportion of equipment in the sample (64.7%) had noproper service agreement support for its preventive maintenance activities. Maintenanceplanning of the sample was perceived as very low by 40 respondents (47.1%), and another 14respondents (16.5%) considered it as low. Accordingly, the practice of maintenance planningin the sample was low.

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0 5 4 17 59 85(0.0%) (5.9%) (4.7%) (20.0%) 69.4% (100%)

20 22 19 24 0 85(23.5%) (25.9%) (22.4%) (28.2%) (0.0%) (100%)

4 15 20 42 4 85(4.7%) (17.6%) (23.6%) (49.4%) (4.7%) (100%)

8 25 15 36 1 85(9.4%) (29.4%) (17.6%) (42.4%) (1.2%) (100%)

17 17 10 34 7 85(20.0%) (20.0%) (11.8%) (40.0%) (8.2%) (100%)

3 14 8 29 31 85(3.5%) (16.5%) (9.4%) (34.1%) (36.5%) (100%)

Speed of faultreporting

Speed of faultinspection

Coordination of therepair process

Managementsupport for repairprocess

Speed of repair

Accuracy of repair

Table 3. Distribution of corrective maintenance support as perceived by operator staff

Source: Survey Data

As shown in Table 3, 59 respondents (69.4%) perceived that speed of fault reporting was veryhigh while 17 respondents (20.0%) viewed that it was high. None of the respondents perceivedit as very low. Hence, the results indicated high speedy fault reporting. In contrast, speed offault inspection was perceived by 49.4% of respondents as either very low or low. Twenty fourrespondents (28.2%) perceived it as high. None of them perceived it as very high. In view ofthe coordination of the repair process, the majority (54.1%) of the respondents perceived ahigher level of coordination. Only 19 respondents viewed it as either very low or low. Therewas a considerable number of neutral responses (23.6%). As for management support, (43.6%) the respondents perceived it as high or very high. The percentage of respondents whoviewed it as either very low or low was 38.8%. There was a significant proportion (17.6%) ofneutral responses. The speed of repair process was viewed by 41respondents (48.2%) aseither very high or high. Thirty four respondents viewed it as either very low or low. Accuracyof repair was rated by the majority of respondents (70.6%) as either very high or high.


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2 5 6 48 24 85(2.4%) (5.9%) (7.1%) (56.4%) 28.2% (100%)

2 10 12 55 6 85(2.4%) (11.8%) (14.1%) (64.6%) (7.1%) (100%)

Availability ofconsumables

Managementsupport for supplyprocess



7 11 3 37 27 85(8.2%) (12.9%) (3.5%) (43.6%) (31.8%) (100%)

0 0 0 31 54 85(0.0%) (0.0%) (0.0%) (36.5%) (63.5%) (100%)

Adequacy of space /infrastructure

Adequacy of powersupply


Table 4. Distribution of supply support as perceived by operator staff

Source: Survey Data

As shown in Table 4, 24 respondents (28.2%) perceived the availability of consumables as veryhigh and 48 respondents (56.4%) viewed as high. Thus, the majority (84.6%) of the sampleopined that the supply of consumables was adequate. The management support for thesupply process was also rated by as very high or high by the majority of respondents (71.7%).

Table 5. Distribution of facility support as perceived by operator staff

Source: Survey Data

As shown in Table 5, facility support was assessed in terms of adequacy of space/infrastructureand adequacy of power supply. Sixty four respondents (75.4%) perceived the provision ofspace and infrastructure as adequate. All respondents perceived provision of power supply asadequate.

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15 4 3 23 40 85(17.6%) (4.7%) (3.5%) (27.1%) (47.1%) (100%)

3 4 4 39 35 85(3.5%) (4.7%) (4.7%) (45.9%) (41.2%) (100%)

Possibility ofsubstitution of staff

Adequacy ofoperator staff



0 18 8 40 19 85(0.0%) (21.2%) (9.4%) (47.1%) (22.3%) (100%)

1 12 5 33 34 85(1.2%) (14.1%) (5.9%) (38.8%) (40.0%) (100%)

Adequacy oftraining of the staff

Adequacy of skill ofthe staff

Table 6. Distribution of staff availability as perceived by the operator staff

Source: Survey Data

As shown in Table 6, staff availability was assessed in terms of possibility of substitution of staffand adequacy of operator staff. Forty respondents (47.1%) perceived the possibility ofsubstitution of staff as very high and 23 respondents (27.1%) viewed it as high. Fifteenrespondents perceived it as very low. The majority of respondents (87.1%) perceived adequacyof staff as very high or high. Only three (8.2%) respondents perceived it as not adequate.

Table 7. Distribution of training and skill support as perceived by operator staff

Source: Survey Data

As shown in Table 7, training and skill support was assessed in terms of adequacy of trainingand adequacy of skill of the operator staff. Nineteen respondents (22.3%) perceived thattraining was highly adequate and 40 respondents (47.1%) perceived it as adequate. Thepercentage of respondents who perceived that training was not adequate was 21.2%. Inregard to skill level, 34 operator staff (40%) perceived that their skill level was very high while33 respondents 38.8%) perceived it as high. The results indicated that the majority of operatorshad an adequate skill level.

2. Operational Availability and Downtime of the Sample

As shown in Table 8, different equipment categories had wide differences in operationalavailability. Infant incubators had the highest level of mean operational availability (72.3%).


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Category of equipment

Type of Department

Type of Hospital

Age in years

Total

X-ray Machine

Spectrophotometer

Flame photometer

Infant incubator

Ventilator

X-ray processor

Dental unit

Radiology

Laboratory

SCBU

ICU

Dental

BH Watupitiwala

BH Gampaha

BH Panadura

BH Avissawella

0 < 2

2 - 4

4 - 6

6 - 8

8 -10

10 <

Mean OperationalAvailability %

45.9

48.6

17.4

72.3

68.5

56.3

52.6

50.4

34.7

72.2

68.5

52.6

53.9

59.0

60.4

55.8

69.2

60.0

60.5

53.2

48.9

48.4

57.1


Flame photometers (17.4%) had the lowest mean operational availability. Each hospital hadachieved operational availability of more than 50%. Equipment in the age category of 0-2years had a higher mean operational availability (69.2%). Equipment in the age category ofmore than 10 years had low mean operational availability (48.4%).

Table 8. Distribution of mean operational availability according to the basic characteristics of thesample

Source: Survey Data

The mean operational availability was 57.1%, indicating that 42.9% of the planned hours hadbeen lost to the patients in selected departments of hospitals. As shown in Figure 1, 25 itemsof equipment (29%) had zero operational availability. The majority of equipment (60%) hadmore than 50% of operational availability. Operational availability was seen clustered at the

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both extremes of a continuum, indicating that equipment was either highly available or notat all available to the patients.

As shown in Figure 2, observed downtime constituted six main categories. They were: cleaning(planned preventive maintenance shutdowns), technical faults, lack of consumables, lack ofpower supply, lack of facilities and lack of staff. Technical faults in the equipment had caused19,712 hours (77%) of the total downtime during the period of study. Lack of infrastructurefacilities had caused 1,899 hours of downtime and lack of consumables had resulted in 1,816hours of downtime. Cleaning of equipment and lack power supply had caused 648.5 hoursand 25.98 hours of downtime respectively.


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Variable Scale of Measurement Total

n % n % n % n %

50 58.8 18 21.2 17 20.0 85 100

10 11.7 35 41.2 40 47.1 85 100

4 4.7 22 25.9 59 69.4 85 100

0 0.0 20 23.5 65 76.5 85 100

6 7.1 17 20.0 62 72.9 85 100

13 15.3 10 11.8 62 72.9 85 100

PreventiveMaintenanceSupport

CorrectiveMaintenanceSupport

Supply Support

Facility Support

Staff availability

Training and skillsupport

Low Moderate High


3. Assessment of Integrated Logistic support

According to the categorical scale developed, the perceived support considerations areillustrated in Table 9. The majority of respondents (58.8%) were of the view the practice ofpreventive maintenance as low. A considerable number of respondents (47.1%) viewedcorrective maintenance support as high and (41.2%) as moderate. High supply support wasperceived by 69.4% of the sample. Facility support and staff availability were perceived ashigh by 76.5% and 72.9% of respondents respectively. This showed that the majority (72.9%)of sample considered training and skill support to be high.

Table 9: Distribution of perceived integrated logistic support

Source: Survey Data

Statistical Analysis

In order to test the hypotheses of the study, each of the ILS variables was correlated withequipment availability and Pearson Product Moment Correlation Co-efficients (r) are shownin Table 10.The absolute value of the correlation coefficient indicates the strength and largerabsolute values indicate stronger relationships. A significance level was determined (alpha =.05) and the significance of the linear relationship of each variable was assessed.

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Table 10: Correlation of ILS variables with equipment availability

Source: Survey Data, *p >.05. **p> .01.> ***p> .001

It was observed that corrective maintenance support had a higher positive correlation withequipment availability and this relationship was statistically significant. This proves the relatedproposition. Preventive maintenance support showed low positive correlation with theequipment availability and its association was statistically significant. This supports the relatedproposition. Supply support and staff availability had weak positive correlations; however, therelationships were statistically significant. Training and skill support had negative weakcorrelation with equipment availability and the relationship was significant; thus, the relatedproposition is rejected. Facility support had the weakest correlation and its relationship wasnot statistically significant.

Discussion

Peabody & Schmitt (1992), Lathwal & Banerjee (2001), and Pardeshi (2005) have used differentstudy designs to find out the degree of equipment availability and factors influencing it. Onthe contrary, this study tests several propositions related to ILS elements in addition to mappingof downtime of the equipment. Certainly, it is difficult to avoid the absolute truth in suchpropositions; however, some arguments shown in the literature in respect of preventivemaintenance support (Hyman and William, 2003; Ridgeway, 2003) are in favour of thegeneration of such propositions. Moreover, looking over the findings of the study may beequally important; hence, it is considered as a priority in the discussion.

A noteworthy downtime has led to suboptimal operational availability of medical equipment(57%) in the selected hospitals. It is above that of the developing countries (20-50%) (Issakov,1994) and that of the Chinese hospitals (41%) (Peabody and Schmitt, 1992). However, thisfinding has to be interpreted cautiously with that of Lathwal and Banerjee (2001) who assessedthe non-functionality of equipment (64%) considering only the effects of technical faults inthe district hospital in Haryana, India. Had he considered other contingency factors for measuringdowntime, the actual equipment availability would have been lower than the figure shown inhis study.

In contrast to the study of Pardeshi (2005), who analyzed the past secondary data usingAuditor General’s Reports in India, it was possible to capture the actual downtime accurately

Variable Correlation Co-efficient (r)

Preventive maintenance support 0.44***

Corrective maintenance support 0.66***

Supply support 0.22**

Facility support 0.20*

Staff availability 0.28**

Training and skill support -0.30***


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by way of observing the actual operation of equipment; thus, it avoids recall bias. Furthermore,technical faults in the equipment were identified as the major share of the downtime (77%).Lack of consumables and lack of facilities resulted in considerable downtime. Operationalavailability among each category of equipment varied to a great extent. However, all fourhospitals achieved almost similar operational availability figures.

Twenty five pieces of equipment (29%) had zero availability. Most of the availability figureswere clustered at two ends of a continuum; hence, it is concluded that most pieces ofequipment are either largely available or not available for patients. The latter phenomenoncould occur in a population of equipment when either the ‘mean time between failures’(MTBF- a Reliability indicator) is short or mean time taken for repairs (MTTR- a Maintainabilityindicator) is high. Pertaining to this sample equipment, frequent, repetitive failures were notobserved, but long lasting downtimes were observed; hence, it is likely that health managersof these hospitals were unable to solve such downtime within a short period of time resultingin prolonged MTTR. If the study had been carried out for a longer period, it would have givenmore insight into this issue.

The study demonstrated that periodic inspections, maintenance planning and serviceagreement support were considerably inadequate. However, a relatively higher quality ofservicing was noticed. This reveals that even though the frequencies of inspections areinsufficient, the competences of maintenance organizations are relatively high. Further,operational availability was statistically associated with preventive maintenance support;hence, overall low preventive maintenance practices may account for the low operationalavailability of the sample (r=0.44).

With reference to corrective maintenance support, initial fault reporting was satisfactory;however, speed of fault inspection was considerably low. The coordination of the repairprocess was relatively high. Higher accuracy of repair was noticed and it indicated theeffectiveness of repairs done by maintenance organizations. Furthermore, higher overallcorrective maintenance support was statistically associated with higher operational availability(r=0.66). Hence, relative low overall corrective maintenance support may be the factor thatmost accounted for suboptimal operational availability of the sample.

The study shows satisfactory evidence relating to availability of consumables and managementsupport given for the supply process. Hence, overall supply support seemed to be adequate.Supply support shows weak correlation (r=0.22) with equipment availability in this study butits relationship was statistically significant. The study was carried out in hospitals in the WesternProvince of Sri Lanka where health managers have more control over the purchase ofconsumables; however, it may have a stronger relationship in any other health care settingwhere the funds are not available on time.

Moreover, focus group discussions of this study revealed a few but critical shortcomings suchas lack of bacterial filters for ICU ventilators, infant incubators and such isolated incidentsmight have considerably affected the patients. Similarly, facility support was satisfactory;however, direct observation revealed a few incidents of non availability of space to keep theequipment. It was seen particularly in the X-ray and Laboratory departments, and downtime


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of each instance was relatively high. Such idling of equipment could be better visualized byobserving the real workplace. Assessment of logistic supportability by way of a questionnairewould not be ideal.

The study demonstrated a higher possibility of substitution of staff, and adequacy of staff wassatisfactory. Overall staff availability seemed to be adequate and it was found that staff availabilitywas not strongly related to increased equipment availability (r=0.28), This may be due to theinclusion of equipment that can be operated by substitute staff (infant incubator, ICU ventilator),and in Sri Lanka, nurses operate these equipment and because of their abundance the possibilityof substitution is high. Hence, staff availability would be an important factor in a differenthealth care setting. Moreover, it may have a stronger relationship with medical equipmentwhich cannot be operated by substitute staff.

Similarly, adequacy of training and skill has been rated as high by the staff whereas focusgroup discussions revealed a scarcity of on-going training programmes. Further, overall trainingand skill support was negatively correlated (r= -0.30) with operational availability. Most of theoperators in health care settings in Sri Lanka may be adequately trained; however, selfassessment of the adequacy of training and skill may not be ideal for capturing the truerelationship. Hence, this area needs more exploration by further research.

Implications for Health Management

The study shows the need for action to improve the operational availability of equipment. As29% of equipment was not ready for use at all throughout the period of study, health managershave to give attention to such equipment in order to utilize them properly. Direct observationwith a view to finding out the causes of downtime is suggested in this regard.

Technical faults constituted a major share of down time; hence, health managers have toprioritize corrective maintenance in their plans. However, reliability of these machines wassatisfactory as there were no frequent faults observed. Maintainability of this equipmentseemed to be low; however, it is recommended to carry out observations for longer periodsso as to catch the indicators such as mean time taken for repair (MTTR) and mean timebetween failures’ (MTBF) before making conclusions in this regard. Other factors affectingmaintainability such as nature of design of the equipment and impact of age, etc. are neededfor further comments on this issue. Hence, further research is recommended.

Overall preventive maintenance support was low; hence, health managers have to improvemost of the aspects of preventive maintenance support such as regularity of periodicinspections, service agreement support and maintenance planning. Further, proper preventivemaintenance programmes have to be established.

Corrective maintenance support was a major determinant of operational availability, and suchmaintenance practices have to be improved. As technical faults were responsible for a largeproportion of downtime, the repair processes have to be expedited. Particularly, attentionshould be paid to speed up fault inspections. Other elements of corrective maintenancesupport such as speed of repair and management support given for repair process have alsoto be improved in order to reduce downtime.


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Even though the other ILS elements were perceived as adequate, there is room forimprovement. The supply of bacterial filters for ventilators and incubators, conduct of in-service training programmes for operator staff and provision of adequate space for keepingequipment are recommended. The impact of these logistic shortages were highlighted in thefocus groups discussions; hence, it is necessary to identify such logistic requirements bydirect observation as even a single incidence of such shortages might cause a significantimpact on patients’ lives.

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