Prerequisite Programs and Food Hygiene in Hospitals: Food Safety Knowledge and Practices of Food Service Staff in Ankara, Turkey •

Prerequisite Programs and Food Hygiene in Hospitals: Food Safety Knowledge and Practices ofFood Service Staff in Ankara, Turkey • Author(s): Murat Bas , PhD; Mehtap Akçil Temel , PhD; Azmi Safak Ersun , BS; Gökhan Kivanç, BSSource: Infection Control and Hospital Epidemiology, Vol. 26, No. 4 (April 2005), pp. 420-424Published by: The University of Chicago Press on behalf of The Society for Healthcare Epidemiology ofAmericaStable URL: http://www.jstor.org/stable/10.1086/502562 .

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Vol. 26 No. 4 INFECTION CONTROL AND HOSPITAL EPIDEMIOLOGY 415

Estimation of the Cumulative Incidenceof Hospital-Acquired Bacteremia FromPrevalence Data: A Formula

Houssein Gbaguidi Haore; Arno Muller; Daniel Talon, PhD; Xavier Bertrand, PhD

ABSTRACTWe evaluated the validity of the formula of Rhame and

Sudderth to estimate the cumulative incidence of nosocomialbacteremia from prevalence studies. The observed cumulativeincidence was threefold higher than the calculated cumulativeincidence. We do not recommend converting prevalence intoincidence data for nosocomial bloodstream infections (InfectControl Hosp Epidemiol 2005;26:415-417).

Hospital-acquired infections increase healthcarecosts, morbidity, and mortality.1 Data on the costs of hospital-acquired infection and the cost-effectiveness ofprevention programs should be made available to policy-makers. However, before these data can be provided, it isnecessary to understand the extent of the problem in eachhealthcare facility. Cumulative incidence is regarded asthe most powerful method to evaluate the impact of hos-pital-acquired infection. However, incidence studies areexpensive because data have to be collected during a longperiod. Point-prevalence studies, which are less expensiveand time-consuming than incidence studies, are also usedto monitor hospital-acquired infection, but they may notprovide a true picture of the pattern of the disease overtime. Some authors have reported that it is possible toestimate the cumulative incidence of hospital-acquiredinfections from prevalence studies by using the formuladescribed by Rhame and Sudderth.2,3 This method makesit possible to convert data on the prevalence of nosocomi-al infections into incidence data. Graves et al. recentlyapplied this method to their data and concluded that it wasa cost-effective alternative to incidence studies.4

We have been conducting incidence and prevalencesurveys of hospital-acquired bacteremia in our hospitalsince 2000. The objectives of this study were to apply theformula of Rhame and Sudderth to our data and to evalu-ate its validity for a single type of nosocomial infection (ie,bacteremia).

METHODS

Setting and Study PeriodBesançon is the largest city in Franche-Comté, a

region of eastern France with approximately 1,000,000inhabitants. Besançon Hospital is a university-affiliated

hospital with approximately 1,200 acute care beds dividedinto 59 units. Approximately 50,000 inpatients are admit-ted per year, for a total of 350,000 patient-days. Data werecollected between 2000 and 2003.

Prevalence Survey The methods used for the prevalence survey have

been defined nationally by l’Institut de Veille Sanitaire.All inpatients were included in the prevalence study. Datawere collected by teams of two individuals (a physicianand a nurse). The clinical records of each patient wereexamined. The following demographic and clinical datawere recorded on a standardized form: date of birth, gen-der, admission date, ward, McCabe index, the presenceof invasive devices (eg, intravascular catheter or urinarycatheter), antimicrobial therapy, and the presence of hos-pital-acquired infections on the day of survey. Bacteremiawas defined according to national guidelines5 that adopt-ed the Centers for Disease Control and Prevention defin-ition of nosocomial bacteremia.6 The number of hospital-acquired cases of bacteremia on the day of the surveywas divided by the number of inpatients on that day toobtain a measure of the prevalence. The prevalence sur-veys were conducted each year in June (from 2000 to2003).

Incidence Survey The bacteremia incidence studies were performed

between October and December every year since 2000.They were carried out according to a nationally defined,laboratory-based methodology also used for the nationalprevalence survey.5,6 The number of new hospital-acquired cases of bacteremia among inpatients admittedduring the period of the survey was divided by the num-ber of inpatients admitted during the same period toobtain the cumulative incidence.

Conversion of Prevalence Data to IncidenceThe formula cumulative incidence = P (LA/LN -

INT), in which P is prevalence, LA is average length ofhospitalization for all patients, LN is average length ofhospitalization for patients with acquired bacteremia, andINT is average interval between admission and onset ofthe nosocomial bacteremia, was used to calculate thecumulative incidence from prevalence results.

Data AnalysisCumulative incidence was calculated from the preva-

lence data using the formula of Rhame and Sudderth andcompared with the observed cumulative incidence.

Concise Communications



416 INFECTION CONTROL AND HOSPITAL EPIDEMIOLOGY April 2005

Confidence intervals for the observed cumulative inci-dence were calculated by Fleiss quadratic 95% intervals.

RESULTS

Prevalence Studies A total of 3,684 patients were investigated. Forty-one

nosocomial bacteremias were found in four prevalencestudies (2000 to 2003), giving an overall prevalence of1.11% (95% confidence interval, 0.81 to 1.52) (Table).

Incidence StudiesA total of 344 nosocomial bacteremias were found

among the 38,212 patients included, giving an overall inci-dence of 0.90%. The average length of hospitalization was8.82 days. Patients with nosocomial bacteremia had an aver-age hospital stay of 47.4 days and a mean interval of 20.4days from admission to the first day of infection (Table).

Conversion of Prevalence Data to Incidence:Application of the Formula of Rhame and Sudderth

We converted the prevalence data to incidence usingthe formula described by Rhame and Sudderth (Table).The overall calculated cumulative incidence was lowerthan the lower confidence limit. The calculated cumula-tive incidence of nosocomial bacteremia for each year waslower than the observed cumulative incidence.

DISCUSSION

Several studies on nosocomial infections have report-ed that the Rhame and Sudderth formula accurately con-verts prevalence data into incidence data.2,3 Gastmeier et al.demonstrated that this formula is also applicable to specif-ic site infections, such as urinary tract infections and surgi-cal-site infections.2 Our study demonstrates that, in ourhospital, prevalence data cannot be converted to incidence

data for nosocomial bloodstream infections. Indeed, theobserved cumulative incidence was threefold higher thanthe calculated cumulative incidence.

The cumulative incidence of nosocomial bacteremiain our hospital was approximately twofold higher thanthat measured in acute care units of French hospitalsusing a similar method (0.90% vs 0.36% to 0.46%).7 Case-mix variation may explain these differences. Indeed, ourhospital had rates similar to those of other university-affil-iated hospitals in France.8

Our prevalence data (from 0.2% to 2.04%) are similarto those observed in other French hospitals.9 Thus, weassume that our observed cumulative incidence andprevalence rate of nosocomial bacteremia represent thetrue picture, taking into account the variations related tosurvey type. The results of the prevalence surveys variedconsiderably (from 0.23% to 2.04%) from one year toanother. Incidence surveys appear to be the most reliablemethod for the surveillance of nosocomial bloodstreaminfections. The limitations of the formula used to estimatecumulative incidence from prevalence data have been dis-cussed by those who developed it and by those who haveapplied it. The main limitation of our study is that preva-lence and incidence surveys were not performed duringthe same period. However, we did not observe variationsof frequencies of bacteremia during a 1-year period.

Our results suggest that this formula is not relevantfor bloodstream infection. In our hospital, patients withsuch infections were hospitalized for much longer thanaverage for all admitted patients (47.4 vs 8.82 days).Furthermore, there is a strong association between sever-ity of illness (high McCabe score, 1 or 2) and the risk ofacquiring nosocomial bloodstream infection (P < .001;odds ratio, 5.87; 95% confidence interval, 2.06 to 16.73).Nosocomial bloodstream infections seem to be the conse-

TABLEPREVALENCE RATE, OBSERVED CUMULATIVE INCIDENCE, AND CALCULATED CUMULATIVE INCIDENCE OF NOSOCOMIAL BACTEREMIA

Characteristic 2000 2001 2002 2003 Total

Prevalence, % (CI95) 2.04 (1.25–3.28) 0.83 (0.39–1.70) 0.23 (0.04–0.93) 1.34 (0.75–2.34) 1.11 (0.81–1.52)NB 18 8 2 13 41Patients 881 965 868 970 3,684

Observed cumulative 1.1 (0.89–1.35) 0.82 (0.66–1.01) 0.92 (0.74–1.14) 0.80 (0.63–1.01) 0.90 (0.81–1.00)incidence, % (CI95)NB 94 87 87 76 344Patients 8,561 10,674 9,465 9,512 38,212

Calculated cumulative 0.86 0.32 0.08 0.29 0.36incidence, %LA, d 10.2 8.00 8.65 8.64 8.82LN, d 44.9 34.7 42.9 70.0 47.4INT, d 20.4 13.9 18.0 30.4 20.4LA/(LN - INT) 0.42 0.38 0.35 0.22 0.33

NB = nosocomial bacteremia; CI95 = 95% confidence interval; LA = average length of stay of all patients; LN = average length of stay of patients with acquired NB; INT = average interval betweenadmission and onset of the NB.



Vol. 26 No. 4 CONCISE COMMUNICATIONS 417

quences of comorbid medical conditions rather than thecauses of increased length of hospital stay. Serious comor-bidities may extend the length of stay sufficiently tonegate any differences in length of stay due to hospital-acquired bacteremia. This may explain why LN - INT,which corresponds to length of hospitalization after initialpositive blood culture (mean, 27 days), exceeds LA.

We were unable to confirm the validity of the pre-dicted cumulative incidence regarding all nosocomialinfections because we have only prevalence and incidencedata for bacteremia. However, we do not recommend thatthis method be used to convert prevalence into incidencedata for nosocomial bloodstream infections.

The authors are from the Service d’Hygiène Hospitalière etd’Epidémiologie Moléculaire, Centre Hospitalier Universitaire JeanMinjoz, Besançon, France.

Address reprint requests to Xavier Bertrand, Service d’HygièneHospitalière et d’Epidémiologie Moléculaire, CHU Jean Minjoz, 25030Besançon, France. [email protected]

REFERENCES1. Jarvis WR. Selected aspects of the socioeconomic impact of nosocomial

infections: morbidity, mortality, cost, and prevention. Infect Control HospEpidemiol 1996;17:552-557.

2. Gastmeier P, Brauer H, Sohr D, et al. Converting incidence and preva-lence data of nosocomial infections: results from eight hospitals. InfectControl Hosp Epidemiol 2001;22:31-34.

3. Delgado-Rodriguez M, Cueto Espinar A, Rodriguez-Contreras Pelayo R,Galvez Vargas R. A practical application of Rhame and Sudderth’s for-mula on nosocomial infection surveillance. Rev Epidemiol SantePublique 1987;35:482-487.

4. Graves N, Nicholls TM, Wong CG, Morris AJ. The prevalence and esti-mates of the cumulative incidence of hospital-acquired infections amongpatients admitted to Auckland District Health Board Hospitals in NewZealand. Infect Control Hosp Epidemiol 2003;24:56-61.

5. National Technical Committee of Nosocomial Infections. 100Recommendations for the Surveillance and Control of NosocomialInfections, ed. 2. Paris: French Ministry of Health; 1999.

6. Garner JS, Jarvis WR, Emori TG, Horan TC, Hughes JM. CDC defini-tions for nosocomial infections, 1988. Am J Infect Control 1988;16:28-40.

7. Branger B, Bussy-Malgrange V, Carbonne A, et al. Nosocomial bac-teremia in France: surveillance data of the coordinating centres fornosocomial infection control. Bulletin Epidémiologique Hebdomadaire2001;50.

8. The Microbiology Surveillance Network of Northern France.Surveillance of nosocomial bacteremia from 1994 to 1996. BulletinEpidémiologique Hebdomadaire 2000;18.

9. Maugat S, Carbonne A, Astagneau P. Significant reduction of nosocomialinfections: stratified analysis of prevalence national studies performed in1996 and 2001 in French north interegion. Pathol Biol 2003;51:483-489.

Medical Errors Detected and Correctedby a Pediatric Infectious DiseasesConsultation Service

Thomas J. Sandora, MD, MPH; Donald A. Goldmann, MD

ABSTRACTErrors occur frequently in healthcare and can adversely

affect outcomes. This prospective study demonstrates that pedi-atric consultants can detect a broad range of errors in the courseof routine work. Many of these errors have the potential to causeharm and can be corrected by the intervention of an infectious dis-eases consultant (Infect Control Hosp Epidemiol 2005;26:417-420).

In 1999, the Institute of Medicine released a reportestimating that at least 44,000 to 98,000 individuals in theUnited States die each year because of medical error.1Since the publication of that report, the focus on patientsafety research has increased dramatically. Most pediatricpatient safety research has focused on medication errorsand adverse drug events. Kaushal et al. performed aprospective study of medication errors at two academicpediatric hospitals and found that 5.7% of medicationorders contained errors. They observed a potentialadverse drug event rate of 1.1% and an adverse drug eventrate of 0.24% (19% of the adverse drug events were pre-ventable).2 Clearly, however, errors in both pediatric andadult care are not confined to the use of medications. Thelandmark Harvard Medical Practice Study documenteda broad range of preventable adverse events.3,4

Classification of medical errors has proved challenging,but the taxonomy proposed by Leape et al. provides a use-ful framework for categorizing errors in diagnosis, treat-ment, and prevention.5

Reported error rates are almost certainly underesti-mates, as many errors are likely to remain undetected orunreported.6,7 The voluntary incident reporting systemsused by most hospitals are particularly insensitive.8

Direct observation of medical care by trained clinical per-sonnel has been shown to produce higher error detectionrates than voluntary reporting,9 but such error surveil-lance is too labor intensive and expensive to be sustain-able outside of a research setting. At academic hospitals,physicians on subspecialty consultation services mayhave a unique opportunity to discover mistakes that aremissed by typical hospital patient safety systems becausetheir advice depends on a comprehensive, detailed reviewof the patient’s management. This study was undertakento quantify and describe the frequency and types of med-ical errors that can be detected in real time by a pediatricinfectious diseases consultation service.

METHODS

Data were collected prospectively for 3 months in2001 and 2002 at a large, urban academic pediatric hospi-tal. The on-service infectious diseases fellow recorded allrecognized medical errors in the care of patients forwhom an infectious diseases physician was consulted.The Institute of Medicine definition of error was used: fail-ure to complete a planned action as intended or use of awrong plan to achieve an aim.1 This broad definition(which characterizes all “errors” as preventable) wasselected to capture a variety of error types.

Error incidence density was calculated by dividingthe total number of errors detected by the total person-time at risk in the population. Errors were independentlyclassified by two infectious diseases physicians into 17types based on a taxonomy modified from the study byLeape et al.5 The kappa statistic was calculated to assessinterrater agreement for error classification. Errors withsignificant potential to cause injury were consideredpotential adverse events; those that caused injury were




considered adverse events. All of the adverse events wit-nessed in our study would be considered “preventableadverse events” by the Institute of Medicine definitionbecause they are attributable to error.1 Adverse eventswere ranked by severity on a 4-point Likert scale (minor,significant, serious, and life-threatening), which has beenused in a previous study of pediatric hospital errors.2 Theauthors also recorded whether detected errors were cor-rected by intervention of the infectious diseases consulta-tion service. Descriptive summary statistics (frequenciesand percentages) were calculated for error types, adverseevents, and correction of errors. Statistical analyses wereperformed using SAS software (version 8.0; SAS Institute,Inc., Cary, NC).

RESULTS

The infectious diseases service performed 205 newconsultations during the 3-month study period. Theseconsultations resulted in a total of 1,423 patient-days ofobservation by the infectious diseases team. Sixty-eighterrors were detected during this period, yielding an errorincidence density of 4.8 errors per 100 patient-days; 1error was detected for every 3 new consultations. Thirty-nine of the errors occurred in the care of immunocompe-tent patients and 25 in immunocompromised patients (4patients did not have immune status recorded). Medicalfloors accounted for 32 errors, surgical floors for 10, andintensive care units for 21. Of the remaining 5 errors, 1occurred in an outpatient clinic and 4 did not have theirlocation recorded. The infectious diseases service wasinvolved in making the error in 11 (16%) of the cases.

Interrater agreement for error classification wasgood (kappa = .73). The most common error type was“wrong medication or wrong dose or schedule,” account-ing for 22% of all witnessed errors (14 of the 15 errors in

this category were wrong doses and 1 was the wrongmedication). Thirteen other error types were detected(Table 1). Table 2 provides descriptions of a selected sam-ple of the observed errors.

Sixty-nine percent of the detected errors were con-sidered potential adverse events and 12% actually resultedin adverse events. Adverse events ranged in severity fromminor to life-threatening; of the 8 adverse events, 1 (12.5%)was considered minor, 1 (12.5%) was significant, 4 (50%)were serious, and 2 (25%) were life-threatening. The twolife-threatening events included a delay in the diagnosis ofa wide-complex ventricular arrhythmia and the develop-ment of pneumococcal sepsis in a patient with a hemoglo-binopathy who was unimmunized and not receivingantibiotic prophylaxis (in the second case, the error in pre-ventive care occurred at another institution). None of theerrors that led to adverse events resulted in permanentinjury or death. Thirty-one errors (46%) were correctedbecause of detection and intervention by the infectious dis-eases team; the corrections included 15 improper antimi-crobial drug doses and 4 errors in infection control pre-cautions. For the errors not corrected by the infectiousdiseases team, most were not correctable because theaction had already occurred (for instance, an unnecessarylaboratory test was performed); in a few cases, someoneother than the infectious diseases team (such as the labo-ratory or the primary care team) corrected an error.

DISCUSSION

This study is the first to address the detection ofmedical errors by pediatric specialists serving as con-sultants. We found that errors can be easily detected byan infectious diseases consultation service in the courseof routine clinical activity in the hospital setting. Errorsoccurred frequently; a rate of one error for every threenew consultations would translate into a substantialnumber of errors if projected across all of the institu-tions in which pediatric infectious diseases consultantsare employed. A wide variety of error types wereobserved in this study, falling into multiple broad cate-gories including diagnosis, treatment, and prevention.Nearly 80% of the errors fell into the top six categories:wrong medication or dose or schedule, error or delay indiagnosis, failure to employ an indicated test, error inperformance of a diagnostic test, error in infection con-trol methods, or failure of communication. More than80% of errors were associated with either a potential oran actual adverse event for patients. Nearly half of thewitnessed errors were corrected as a result of our moni-toring and intervention, emphasizing the potentialimpact of a vigilant infectious diseases consultation teamon quality of patient care.

Importantly, this study demonstrates that improve-ments in patient safety can be achieved by creative use ofexisting resources within a hospital system. We intention-ally did not set out to perform a comprehensive, hospital-wide review of clinical practice and medical records. Suchreviews are impractical and unsustainable without sub-

TABLE 1FREQUENCY OF ERRORS BY TYPE

No. (%%) ofType of Error Total Errors

Wrong medication or wrong dose or schedule 15 (22)Error or delay in diagnosis 12 (18)Failure to employ indicated test 10 (15)Error in performance of a diagnostic test 6 (9)Error in infection control methods 5 (7)Failure of communication 4 (6)Failure to act on results of testing or monitoring 3 (4)Failure to provide prophylactic treatment 3 (4)Use of inappropriate test 3 (4)Error in administration or method of using a treatment 2 (3)Error in patient identification 2 (3)Avoidable delay in treatment 1 (1.5)Inappropriate (not indicated) care 1 (1.5)Other systems failure or error 1 (1.5)




stantial research funding. Many hospitals, including ours,do have aggressive, multidimensional programs to detect,intercept, and prevent errors. For example, our programincludes (but is not limited to) voluntary incident report-ing, interception of errors by ward-based clinical pharma-cists, real-time patient safety audits, concurrent surveil-lance for nosocomial infections and surgical complications,verification of compliance with the patient safety goals of the Joint Commission on Accreditation of HealthcareOrganizations, standardized physician order templatesand practice guidelines, nursing double-checks of criticalpatient care practices, and staged implementation of com-puterized physician order entry. Trained personnel alsofacilitate root cause analysis and failure mode and effectsanalysis. However, despite these proactive efforts, manyerrors, such as those detected by consultants in this study,are not discovered by current systems. The novel andimportant finding of this study is that a prepared consul-tant can discover a wide variety of additional errors duringroutine work without additional expenditure of resourcesor time commitment.

Frank reporting of medical errors in a blame-free,“culture of patient safety” environment is critical to under-standing the epidemiology, etiology, and prevention oferrors. Root cause analysis of errors permits elucidation ofsystems problems and human factors that contribute to errors. The Joint Commission on Accreditation ofHealthcare Organizations,10 the Association of Litigationand Risk Management/Clinical Risk Unit,11 and otherorganizations have published paradigms for investigationof errors.12,13 In addition to the analysis of errors that havealready occurred, rigorous examination of error-pronesteps in healthcare delivery systems is essential for errorprevention. Industrial, systems-oriented, error-proofingstrategies that employ engineering principles, such as failure mode and effects analysis and hazard analysis criti-cal control points, show promise in healthcare settings.14,15

Multidisciplinary teams working across traditional depart-mental and professional boundaries are required toaddress complex healthcare systems. Ideally, such teamsshould address errors detected by consultation services,facilitated by the institution’s risk management and qualityimprovement programs. We did not report errors to riskmanagement during this study. In general, errors arereported by the clinical service, the department in whichthe errors occur, or both. However, it would be advisablefor consultants to ensure that the errors they detect arereported, as they may have insights that would contributeto a root cause analysis. Errors detected in this study wereprimarily corrected on an individual patient basis,although one systematic intervention did occur as a resultof our work (the microbiology laboratory began a rigoroussystems improvement project to document and follow upon all errors related to diagnostic testing).

This study has several limitations. We recorded onlyerrors that occurred in patients being observed by theinfectious diseases team, and we focused only on infec-tious diseases issues (as opposed to other types of patientcare errors). Because only one busy infectious diseasesfellow was performing primary data collection, it is likelythat other errors occurred but were not recognized.These data may not be generalizable to healthcare set-tings other than pediatric academic hospitals, althoughmany of these error types certainly can occur in settingssuch as an outpatient clinic. Some errors did not fall neat-ly into one category, and thus far no universal classifica-tion system has been accepted.13 Other observers mightcategorize these errors differently, although our highdegree of interrater agreement is reassuring in thatregard. Finally, determining a direct causal link betweenan action and a subsequent adverse event was challengingin several cases; we used a broad interpretation scheme tohighlight a wide variety of potential errors and their con-sequences.

TABLE 2EXAMPLES OF ERRORS DETECTED

Ceftriaxone dose was too highAmikacin level sent but the patient did not receive amikacinParainfluenza 3 DFA results listed as both positive and negative simultaneouslyVancomycin given without checking creatinine; the patient was found to be in renal failure with a vancomycin trough of 81 µg/mLEchocardiogram showed “tip of CVL in innominate vein” but the patient did not have a CVLBlood culture from outside hospital was not checkedBMT patient received a GCSF dose of 1 µg/kg instead of 10 µg/kgCovering weekend fellow put a progress note in the wrong chartPatient on contact precautions was examined without gown and glovesPleural fluid sent for diagnostic studies but no pH was orderedKirby–Bauer done on Pseudomonas isolate but the ciprofloxacin disk fell off the platePiperacillin–tazobactam dose was not adjusted for elevated creatinineOncology patient with rotavirus infection was in the playroom

DFA = direct fluorescence antibody; CVL = central venous line; BMT = bone marrow transplant; GCSF = granulocyte colony-stimulating factor.




We have shown that a wide variety of medical errorscan be detected by a pediatric infectious diseases consul-tation service in the course of routine work. Many ofthese errors can result in adverse events, and most can becorrected by intervention of the consultant. Mechanismsshould be developed to facilitate feedback about errors toproviders who request consultations as well as to hospitalrisk management and patient safety programs. Futureeffort might focus on the development of a standardizeddata collection instrument for error detection by consult-ing physicians. A more formal structure for the detectionand reporting of errors could have wide applicability notonly for infectious diseases physicians but also for a vari-ety of other specialty consultation services in both pedi-atric and adult medicine.

The authors are from the Children’s Hospital Boston, HarvardMedical School, Boston, Massachusetts.

Address reprint requests to Thomas J. Sandora, MD, MPH,Division of Infectious Diseases, Children’s Hospital Boston, 300Longwood Avenue LO 650, Boston, MA 02115. [email protected]

Supported by the Glaser Pediatric Research Network (TJS). Presented in part at the 41st Annual Meeting of the Infectious

Diseases Society of America; October 9-12, 2003; San Diego, CA.

REFERENCES1. Kohn LT, Corrigan JM, Donaldson MS, eds. To Err Is Human:

Building a Safer Health System. Washington, DC: National AcademyPress; 2000.

2. Kaushal R, Bates DW, Landrigan C, et al. Medication errors and adverse drug events in pediatric inpatients. JAMA 2001;285:2114-2120.

3. Brennan TA, Leape LL, Laird NM, et al. Incidence of adverse events andnegligence in hospitalized patients: results of the Harvard MedicalPractice Study I. N Engl J Med 1991;324:370-376.

4. Leape LL, Brennan TA, Laird N, et al. The nature of adverse events inhospitalized patients: results of the Harvard Medical Practice Study II.N Engl J Med 1991;324:377-384.

5. Leape LL, Lawthers AG, Brennan TA, Johnson WG. Preventing medicalinjury. QRB: Quality Review Bulletin 1993;19:144-149.

6. Vincent C, Stanhope N, Crowley-Murphy M. Reasons for not report-ing adverse incidents: an empirical study. J Eval Clin Pract 1999;5:13-21.

7. Murff HJ, Patel VL, Hripcsak G, Bates DW. Detecting adverse events forpatient safety research: a review of current methodologies. J BiomedInform 2003;36:131-143.

8. Stanhope N, Crowley-Murphy M, Vincent C, O’Connor AM, Taylor-Adams SE. An evaluation of adverse incident reporting. J Eval Clin Pract1999;5:5-12.

9. Flynn EA, Barker KN, Pepper GA, Bates DW, Mikeal RL. Comparison ofmethods for detecting medication errors in 36 hospitals and skilled-nursing facilities. Am J Health Syst Pharm 2002;59:436-446.

10. Joint Commission on Accreditation of Healthcare Organizations. Our Commitment to Patient Safety: Sentinel Event Policy. OakbrookTerrace, IL: Joint Commission on Accreditation of HealthcareOrganizations; 2004. Available at www.jcaho.org/general+public/patient+safety/index.htm#two. Accessed January 8, 2004.

11. Vincent C, Taylor-Adams S, Chapman EJ, et al. How to investigate andanalyse clinical incidents: clinical risk unit and association of litigationand risk management protocol. BMJ 2000;320:777-781.

12. Australian Patient Safety Foundation (APSF). The Australian IncidentMonitoring System (AIMS). Adelaide, Australia: Australian PatientSafety Foundation; 1998. Available at www.apsf.net.au/products.html.Accessed January 28, 2004.

13. Aspden P, Corrigan JM, Wolcott J, Erickson SM, eds. Patient Safety:Achieving a New Standard for Care. Washington, DC: National AcademyPress; 2003.

14. Spath PL. Using failure mode and effects analysis to improve patientsafety. AORN J 2003;78:16-37, 41-14.

15. Baird DR, Henry M, Liddell KG, Mitchell CM, Sneddon JG. Post-opera-tive endophthalmitis: the application of hazard analysis critical controlpoints (HACCP) to an infection control problem. J Hosp Infect2001;49:14-22.

Prerequisite Programs and FoodHygiene in Hospitals: Food SafetyKnowledge and Practices of FoodService Staff in Ankara, Turkey

Murat Bas, PhD; Mehtap Akçil Temel, PhD; Azmi Safak Ersun, BS; Gökhan Kivanç, BS

ABSTRACTOur objective was to determine food safety practices relat-

ed to prerequisite program implementation in hospital food services in Turkey. Staff often lack basic food hygiene knowl-edge. Problems of implementing HACCP and prerequisite pro-grams in hospitals include lack of food hygiene managementtraining, lack of financial resources, and inadequate equipmentand environment (Infect Control Hosp Epidemiol 2005;26:420-424).

Hospital food service systems are considered one ofthe most complicated production processes in the hospi-tality sector.1 Hospital outbreaks of food-borne diseaseaffect patients, personnel, and visitors. Mishandling foodfacilitates pathogen proliferation and disease, especiallyamong patients with impaired immunity or achlorhydria.A major hospital goal is to provide food that is microbio-logically safe because hospitalized patients are more sus-ceptible to infection and consequent morbidity and mor-tality.2 There is a growing population (ie, pregnantwomen, the elderly, the very young, and individuals whoare immunocompromised) that is particularly susceptibleto food-borne illnesses.3

The World Health Organization (WHO) has pub-lished a definition for prerequisite: “practices and condi-tions needed before and during the implementation ofHazard Analysis and Critical Control Point (HACCP) andwhich are essential for food safety.” These are describedin the Codex Alimentarius Commission’s GeneralPrinciples of Food Hygiene and other Codes of Practice.4Prerequisite programs include supplier control, writtenspecifications, written cleaning and sanitation procedures,and documented employee training.5

Our objectives were to evaluate current food han-dling practices, the presence of prerequisite programs,and food safety knowledge of staff at hospital food ser-vices in Ankara, Turkey, and to provide baseline data forimplementing HACCP in hospital food service.

METHODS

Food Safety Knowledge Questionnaire Our survey was conducted from October 2003 to

February 2004 and involved 20 government and privatehospitals in Ankara, Turkey. We obtained data about foodservice staff knowledge of food poisoning, personalhygiene, cross-contamination, high-risk food groups,temperature control, cleaning, and demographicsof food service staf f. A score lower than 50% on the questionnaire was considered poor knowl-edge.




Prerequisite Programs Questionnaire DesignThe 20 hospital food service assessments were con-

ducted during a 5-month period. The food service directorof each hospital was visited by personnel trained inHACCP prerequisite programs who conducted face-to-face interviews and administered the questionnaire. Thequestionnaire included questions about the number offood service staff, hospital beds, and meals served; imple-mentation of HACCP systems; record keeping; personalhygiene practices; good manufacturing practices andhygiene procedures; environmental hygiene; equipmentcleaning and sanitation; pest control; and general sanita-tion procedures; and specific questions on the flow of food(purchasing, receiving, storage, production, and service).All questions were based on the guidelines of the NationalAdvisory Committee on Microbiological Criteria forFoods6 and the Servesafe Course Book.7 Each responsewas coded on a 4-point Likert scale: full compliance (3points) was defined as full compliance with good manu-facturing practices, sanitation, pest control, or HACCPrequirements; minor deficiency (2 points) was defined asa minor deficiency of good manufacturing practices, sani-tation, pest control, or HACCP requirements (little poten-tial hazard to the product); major deficiency (1 point) wasdefined as a major deficiency of good manufacturing prac-tices, sanitation, pest control, or HACCP requirements(potential hazard to the product exists); and noncompli-ance (0 points) was defined as serious deficiencies ofgood manufacturing practices, sanitation, pest control, orHACCP requirements (actual hazard to the productexists). Scores ranged from 0 to 384; all scores were con-verted to a 100-point score.

Field ObservationObservations of employee food-handling practices

were conducted during the lunch meal period. Theyinvolved 6 hours of observation from meal preparation toservice. Two observers were trained to conduct observa-tions. In addition to observations, objective measure-ments (ie, food or refrigerator temperatures) were made.Food temperatures were checked with calibrated, tip-sen-sitive digital thermometers (FW 2000, Cooper InstrumentCorp., Middlefield, CT). Thermometers (DFP450W,Cooper Instrument Corp.) were used to check high-tem-perature dishwashing machines.

Statistical AnalysisAll analyses were performed using SPSS software

(version 11.0 for Windows; SPSS, Inc., Chicago, IL).Statistical significance was set at a P value of less than .05.The differences between trained and untrained staff meanvalues were determined by parametric (independent sam-ple t test) test. The chi-square test was used to comparethe percentage of the occupational level.

RESULTS

Three hundred fifty (90.9%) of 385 food service staffreplied to the questionnaire and 16 (80%) of 20 food ser-

vice directors replied to the prerequisite questionnaire.Overall, 65.1% of food service staff had received food safe-ty training. The mean number of food service staff was41.9 ± 21.8, the mean number of meals prepared each daywas 1452.5 ± 701.1, and the mean number of beds was616.5 ± 467.1. The mean personal hygiene practices andoperational control procedures scores on the prerequisitequestionnaire were 55.3% ± 14.7% and 63.7% ± 8.6%, respec-tively (100 possible points). The overall mean score on theprerequisite questionnaire for hospital food service was57.5% ± 6.4%. The overall score for the prerequisite ques-tionnaire was higher in private hospitals than in govern-ment hospitals (P < .05).

Thirty-nine percent of food service staff correctlyanswered that the temperature of food in a refrigeratorshould be 5°C or lower (Table 1). For hot food, 19.1%thought that bacteria grew at a temperature of 73°C, andonly 48.9% were able to specify the correct temperature.The percentage of correct answers to the food safetyknowledge questionnaire was higher for trained food ser-vice staff than for untrained staff (P < .05). Approximately75% of surveyed food service staff believed one could tellwhether food was contaminated with food poisoning bac-teria and thus unsafe to eat by visual, olfactory, or tastechecks.

Overall results indicated that proper food handlingpractices were not being followed in many hospital foodservices (Table 2). Most hospital food services were notmeasuring and recording food temperatures (95.0%).Taking and recording endpoint temperatures of allcooked foods was implemented by 5.0% of hospital foodservice directors. For food temperatures taken by thesurvey team, the temperatures of cold foods were fre-quently higher than the recommended temperature(4°C).

DISCUSSION

Our survey shows that hospitals in Ankara are notready to implement HACCP because only four hospitalfood service directors reported having had always imple-mented prerequisite programs and one hospital food ser-vice director reported having had implemented HACCPprograms. This is lower than in an Italian study in which54% of hospitals had HACCP programs in place.8

Because temperature treatment is frequently thecritical control point in a production process, poor tem-perature understanding is a major hindrance to effectiveHACCP implementation.9,10 In our study, time and tem-perature errors and inadequate handwashing are only twopractices that were identified as problems in hospitals.Most hospital food services were not taking and record-ing food temperatures. Food thawing at room tempera-ture also was commonly observed. Hot or cold foods werenot held at recommended temperatures.

In a study by the Food and Drug Administration,improper holding and time temperature relationships hadthe lowest compliance (60.4%), followed by personalhygiene (81.3%). Sixty-one percent of hospitals did not keep




cold foods cold enough, and improper or inadequate hand-washing was observed in 42.0% of hospitals.11 We foundthat only 10.0% of hospitals had written manuals for food

hygiene practice. This was lower than reported in anIranian study (35.5%).2 More than 90.0% of directors report-ed no standard operating procedures for thawing foods,

TABLE 1FOOD SAFETY KNOWLEDGE OF HOSPITAL FOOD SERVICE STAFF

Food Hygiene TrainingYes (n = 228) No (n = 122) Total (n = 350)

Question Answer No. %% No. %% No. %% P

Hot food must be kept above which temperature? 25°C 26 11.4 32 26.2 58 16.6 .000*

47°C 12 5.3 15 12.3 27 7.7

63°C 126 55.3 45 36.9 171 48.9

73°C 55 24.1 12 9.8 67 19.1

Not sure 9 3.9 18 14.8 27 7.7

Which of the following temperatures do -10°C 27 11.8 21 17.2 48 13.7 .000*

bacteria readily multiply at? 25°C 125 54.8 38 31.1 163 46.6

75°C 37 16.2 9 7.4 46 13.1

120°C 18 7.9 15 12.3 33 9.4

Not sure 21 9.2 39 32.0 60 17.1

The temperature inside a refrigerator should 10°C 12 5.3 3 2.5 15 4.3 .004*

be at or below which temperature? 5°C 81 35.5 56 45.9 137 39.1

0°C 50 21.9 21 17.2 71 20.3

-20°C 79 34.6 30 24.6 109 31.1

Not sure 6 2.6 12 9.8 18 5.1

The temperature danger zone for food is between: -18°C and 0°C 12 5.3 3 2.5 15 4.3 .000*

0°C and 5°C 3 1.3 9 7.4 12 3.4

5°C and 63°C 159 69.7 53 43.4 212 60.6

73°C and 90°C 18 7.9 30 24.6 48 13.7

Not sure 36 15.8 27 22.1 63 18.0

For cooking chicken, the internal temperature 55°C 35 15.4 9 7.4 44 12.6 .020*

should reach: 60°C 35 15.4 18 14.8 53 15.1

45°C 34 14.9 12 9.8 46 13.1

74°C 109 47.8 65 53.3 174 49.7

Not sure 15 6.6 18 14.8 33 9.4

After cooking, potentially hazardous foods must 1 hour 25 11.0 3 2.5 28 8.0 .000*

be cooled to 21°C within 2 hours and then cooled 2 hours 70 30.7 15 12.3 85 24.3

to 4°C within a maximum of: 3 hours 6 2.6 0 0.0 6 1.7

4 hours 106 46.5 65 53.3 171 48.9

Not sure 21 9.2 39 32.0 60 17.1

If food is contaminated with food poisoning Tasting it 62 27.2 30 24.6 92 26.3 .000*

bacteria, you can normally tell by: Smelling it 70 30.7 27 22.1 97 27.7

Looking it 24 10.5 47 38.5 71 20.3

None of these 69 30.3 12 9.8 81 23.1

Not sure 3 1.3 6 4.9 9 2.6

At body heat (37°C), what will food poisoning Die 36 15.8 3 2.5 39 11.1 .000*

bacteria do? Not grow 6 2.6 0 0.0 6 1.7

Grow quickly 127 55.7 77 63.1 204 58.3

Grow slowly 38 16.7 12 9.8 50 14.3

Not sure 21 9.2 30 24.6 51 14.6

Note. Bolding indicates expected correct answer.*Significantly different between trained and untrained food service staff (P < .05).




taking and recording temperatures, storing food and chem-icals, cleaning and sanitizing, and handling leftovers.Training is a prerequisite; 65.1% of hospital food servicestaff received some basic food hygiene training.Nevertheless, food safety knowledge scores were low (49.9± 11.1). Only 48.9% of respondents knew the correct tem-peratures for storage of hot ready-to-eat foods. This is sim-ilar to an Italian study8 in which 47.7% of respondents knewthese values and higher than an Iranian study2 in which9.4% knew these values. In our observations, sanitizer con-centrations were never checked or recorded in the hospitalfood service. In nearly 50% of hospitals, physical conditionswere inadequate. In most hospitals, there were inadequatenumbers of handwashing stations, store rooms, or toiletsfor food service staff. Inadequate handwashing (ie, notusing sanitizer, inadequate length of time, or poor tech-nique) was frequently observed. Our findings are consis-tent with those of previous studies, which have indicatedthat there were problems with prerequisites programs inmany hospitals throughout the world.2,8

Our study demonstrates that food service staff have

a lack of food safety knowledge. The significance ofHACCP implementation needs to be clarified and empha-sized in hospital food service because a lack of prerequi-sites was identified as the main barrier to compliance.Developing and implementing written standard operatingprocedures in hospital food service operations is one of the first steps to building effective HACCP sys-tems.

Dr. Bas, Mr. Ersun, and Mr. Kivanç are from the Department ofNutrition and Dietetics; and Dr. Temel is from the Department ofStatistic and Computer Sciences, Baskent University, Ankara, Turkey.

Address reprint requests to Murat Bas, PhD, Baskent University,Health Sciences Faculty, Department of Nutrition and Dietetics,Baglica Kampüsü, Eskisehir Yolu 20.km, 06530, Ankara, [email protected]

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of hazard analysis and critical control points in hospital catering.Managing Service Quality 1997;7:150-156.

2. Askarian M, Kabir G, Aminbaig M, Memish ZA, Jafari P. Knowledge, atti-tudes, and practices of food service staff regarding food hygiene inShiraz, Iran. Infect Control Hosp Epidemiol 2004;25:16-20.

3. Woteki CE, Facinoli SL, Schor D. Keep food safe to eat, healthful food

TABLE 2FOOD SAFETY PRACTICES OF THE HOSPITAL FOOD SERVICE (N = 20)

Yes NoFood Safety Practices No. %% No. %%

Personal*Proper personal hygiene practices were observed 7 35.0 13 65.0Staff were observed with hair restraints and clean uniforms 11 55.0 9 45.0Staff were observed washing hands as needed 10 50.0 10 50.0

Building, grounds, and environment*Proper handwashing sink is located in the food preparation area 10 50.0 10 50.0Food contact surfaces are clean, designated, and maintained 15 75.0 5 35.0Areas are properly ventilated, cleaned, and maintained 7 35.0 13 65.0Non-food contact surfaces are cleaned and maintained 15 75.0 5 25.0

Equipment*All small equipment and utensils are sanitized between uses 10 50.0 10 50.0Work surfaces are clean to sight and touch 9 45.0 11 55.0

Product and process control*Foods are properly labeled and dated 10 50.0 10 50.0Hot foods held at higher than 63°C 6 30.0 14 70.0Cold foods held at 4°C or below 8 40.0 12 60.0Leftovers are reheated rapidly to 74°C in 2 hours 4 20.0 16 80.0Rapid cooling methods in place to achieve 60°C to 21°C in 2 hours; 5 25.0 15 75.0

21°C to 4°C in 4 additional hoursTake and record endpoint temperatures of all cooked food 1 5.0 19 95.0Take and record temperature of food during cooling 1 5.0 19 95.0Take and record temperature of food during reheating 1 5.0 19 95.0Take and record dish washing machine temperature - - 20 100.0Dry storage temperatures are between 10°C and 21°C 14 70.0 6 30.0Raw and cooked foods are stored separately 9 45.0 11 55.0Food is stored at least 6 inches above the floor throughout the facility 6 30.0 14 70.0No evidence of pests is present 12 60.0 8 40.0

*Observations by the research team.




must be safe as well as nutritious. J Nutr 2001;131:502-509.4. World Health Organization (WHO). Strategies for Implementing HACCP

in Small and/or Less Developed Businesses, The Hague, June 16-19, 1999.Geneva: World Health Organization; 1999. Available at www.who.int/foodsafety/publications.

5. Bryan FL. Teaching HACCP techniques to food processors and regula-tory officials. Dairy, Food and Environmental Sanitation 1991;11:562-568.

6. National Advisory Committee on Microbiological Criteria for Foods.Hazard analysis and critical control point principles and applicationguidelines. J Food Prot 1998;61:1246-1259.

7. The Educational Foundation of the National Restaurant Association.Serving Safe Food: A Practical Approach to Food Safety. Chicago: The Educational Foundation of the National Restaurant Association; 1995.

8. Angelillo IF, Viggiani NMA, Greco RM, Rito D. HACCP and foodhygiene in hospitals: knowledge, attitudes, and practices of food ser-vices staff in Calabria, Italy. Infect Control Hosp Epidemiol 2001;22:363-369.

9. Fuerst R. Frobisher and Fuerst’s microbiology in health and disease:foods as vectors of microbial disease. In: Sanitation in Food Handling,ed. 15. Philadelphia: W. B. Saunders; 1983:418-433.

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Documents

Prerequisite Programs and Food Hygiene in Hospitals: Food Safety Knowledge and Practices of Food Service Staff in Ankara, Turkey •