Cost awareness among healthcare professionals at a South African hospital: A cross-sectional survey.
There is a gap in the SA literature with regard to HCPs' cost awareness, which we aim to address. The objective of our study was to assess SA HCPs' knowledge of healthcare costs and to identify factors that influence cost awareness. Specifically, we sought to determine whether HCPs at a major tertiary academic hospital were aware of the cost of 15 selected drugs, medical products, disposables and investigations commonly used in their practice, and whether there are differences in cost estimation accuracy between groups of HCPs according to levels of training, specialty and involvement in private practice. We also sought to determine whether surveyed HCPs received training relating to cost management during their studies or at any stage during their practice.
This was a single-centre cross-sectional survey conducted by means of a standardised questionnaire. The study was conducted at four clinical departments at Chris Hani Baragwanath Academic Hospital (CHBAH), Johannesburg, SA. This tertiary academic hospital is affiliated to the University of the Witwatersrand, Johannesburg.
The questionnaire assessed knowledge of the cost of 15 items commonly used in clinical practice. The items included 4 drugs, 5 intravenous fluids, 3 disposable items and 3 laboratory tests. HCPs were asked about prior education or training relating to cost awareness, as well as their attitudes towards the availability of cost information and its influence on patient care.
Cost was defined as the 'single exit price', which was the current price set for CHBAH by the manufacturer or importer of a medicine or disposable combined with the logistics fee and value-added tax. The National Health Laboratory Service provided the cost of the laboratory investigations. Cost estimations were considered correct if the absolute value of the log deviation was <0.2.
Ethical approval was obtained from the Human Research Ethics Committee (medical) of the University of the Witwatersrand before commencement of the study (ref. no. M150337). Participants were de-identified to ensure anonymity. Participating HCPs included house officers, registrars, specialists, clinical nurses and nursing assistants employed in the departments of anaesthesia, intensive care, obstetrics and gynaecology, and general surgery.
Data analysis was conducted using the open-source software R (3.2.2). The mean log deviation and standard deviation (SD) of the estimated cost of each item were calculated for age, gender, level of training, number of years in clinical practice, various groups of HCPs (intensive care, general surgery, obstetrics and gynaecology, anaesthesia) and private practice involvement. Log deviation was taken as the natural logarithm of the estimate divided by the true cost.
Accuracy was assessed by calculating the mean, median, SD, confidence interval (CI) and interquantile ranges of the log deviation per group. Log deviations with an absolute value of <0.2 were regarded as accurate. The frequency of correct estimates, underestimates and overestimates was calculated. Accuracy was compared using box plots between level of training, number of years in healthcare service, various groups of HCPs according to department (intensive care, general surgery, obstetrics and gynaecology, anaesthesia) and private practice involvement. Differences in means were investigated using analysis of variance (ANOVA). Levels of p<0.05 were accepted as significant.
Of the 587 questionnaires distributed, 271 were received (response rate 46.16%). Of these, 26 were excluded (13 were completed by medical students, 4 by members of departments not part of the study sample, and 9 did not answer 7 or more cost estimation questions). The demographics of the respondents are shown in Table 1.
The mean period of time in clinical practice was 14.25 (range 0.00 42.00) years. Ninety-seven (39.6%) participants stated involvement in private practice, 143 (58.4%) were not involved and 5 (2.0 %) did not respond to this question. The average time of involvement in private practice was 6.57 (median 4.00; range 0.01 - 30.00) years. A total of 152 (62.04%) did not respond to this question.
Overall, cost estimation accuracy was low (median 0.60; SD 1.99) and differed widely between items. Cheaper items were more likely to be overestimated and expensive items to be underestimated (Fig. 1).
There were no significant differences in cost accuracy between departments (p=0.078), position in department (p=0.167) or number of years in clinical practice (p=0.187). Similarly, involvement in private practice was not significantly associated with a difference in accuracy of cost estimations (p=0.934). Factors influencing cost accuracy are illustrated in Table 2.
Respondents were also asked if they used any other medical product or investigation that was not part of the listed items of which they knew the price. Thirty-eight (15.51%) indicated 'yes', 210 (85.71%) indicated 'no' and 6 (2.44%) did not respond to this question. Thirty-nine (15.91%) of those surveyed indicated that they had received healthcare cost management education at any point during their training, while the majority (n=209; 85.30%) indicated that they had not. Six participants (2.44%) did not respond to this question.
HCPs were asked whether they require the cost information of drugs, equipment and disposables to be readily available. The majority requested more readily available information regarding the cost of such health resources (yes: n=226, 92.24%; no: n=23, 9.38%; not stated: n=5; 2.04%). Furthermore, the majority of respondents felt that knowledge of cost information of medical consumables and services would improve both resource management (98.36%) and patient care (83.67%). Of those surveyed, 16.73% thought that knowledge of cost information of medical products and services would negatively impact patient care.
The results of this study are in keeping with those of other studies on cost awareness of HCPs that have found cost estimation accuracy to be low. [3,9-12] In a systematic review by Allan et al.,  investigating doctors' knowledge of the cost of medications, a low cost estimation accuracy was found, with 31% of estimates being within 20% or 25% of the true cost.
A survey conducted by Bade et al.  in three New Zealand hospitals, showed that only 18.6% of estimates fell within [+ or -] 25% of true cost. Cost (51.2%) was underestimated in their study. A survey conducted among anaesthetic staff in a UK practice showed more accurate responses than other studies.  The definition of accuracy was not stated in their methodology. Forty-seven percent of estimates were within 50% of the true cost and 75% within 100%.  The cost of expensive items was underestimated and that of cheap items was consistently overestimated.  HCPs also indicated that they had limited training in cost awareness measures, would like cost information to be readily available, and that such information would possibly improve patient outcomes.
The trend towards underestimating the prices of expensive drugs and overestimating those of less expensive drugs, as evident in our study, has been found in other similar studies. [3,11] This finding is not surprising, considering the method that is often used to estimate cost accuracy, i.e. estimated price or real price deviation from true cost. [9,10,12] The overestimation of inexpensive drugs and equipment is inherent in studies that use percent deviation from true cost in assessing cost accuracy. [9,10,12] For example, a drug that costs ZAR1, but is overestimated by a participant to cost ZAR2, is assessed as being 100% overestimated by such a method (albeit still correctly assessed as being cheap). However, an expensive item that costs ZAR100 000 might be estimated to cost ZAR150 000 by a study participant, with a resultant 50% overestimation. Firstly, it is unusual for a cost estimation of an item to be a negative number. Secondly, participants may overestimate an item by a magnitude of 300%, but are unlikely to underestimate such an item as costing 300% less, i.e. a negative number. One can underestimate by a maximum of 100%, but overestimate by a larger factor, which emphasises overestimation, especially for cheap items. The use of percentage deviation overquantifies overestimates and under-quantifies underestimates (which can be at most 100%; overestimates can be [greater than or equal to] 100%). Hence, it is more appropriate to use log deviation, as has been done in this study. Log deviation quantifies the scale of mis-estimations and minimises this effect by measuring the scale factor of the estimations.
With regard to factors affecting cost awarenss, a study by Glickman et al.  showed that younger rather than older physicians were more likely to make correct estimates, and specialists in internal medicine were less likely to make correct estimates than those from other disciplines. Allan et al.'s  systematic review of physician awareness of drug cost, by investigating doctors' knowledge of the cost of medications and factors influencing cost awareness, not only showed a low cost estimation accuracy but also that high-cost items were more accurately estimated than inexpensive ones. Doctors thought that cost information would improve their prescribing, but these data were not accessible.  Three studies in this review found cost estimations by non-academic physicians more accurate than those by academic physicians. 
In the survey conducted by Bade and Hoogerbrug,  no significant differences in accuracy were found between consultants, registrars and house officers or between consultants working in private and those in both private and public practice.
The current study found no significant differences in cost estimation accuracy between departments based on number of years in clinical practice.
Numerous studies have found that there is no difference in cost estimation accuracy between HCPs at various levels of training and experience, finding no such differences among medical students, residents, faculty physicians, specialists and physicians. [11,14,15] We found that private practice involvement does not significantly influence cost estimation accuracy.
Our study highlights that HCPs perceive that they do not have sufficient training relating to cost awareness. Participants indicated that they would like cost information to be readily available and that knowledge thereof would not negatively affect patient care.
Educational interventions aimed at the teaching of cost consciousness have yielded conflicting results. [15,16] Radiological cost related to abdominal imaging was significantly reduced in one study after an educational cost awareness intervention, whereas readmission risk coupled with a non-significant cost difference between the intervention and control group was evident in another study that aimed to reduce costs by a similar educational intervention. [15,16] This highlights that educational interventions aimed at reducing costs have to be carefully structured before implementation and that they may not necessarily lead to the overall reduction of costs. A simple intervention might be to provide and make readily accessible cost information relating to tests, disposables and equipment; the effect of this has been shown to persist during the period that the cost information is available.  Awareness of the lack of knowledge of healthcare-associated costs and the desire to improve such knowledge highlight the progressive attitudes towards cost awareness and cost consciousness in this group. However, despite working in a resource-limited setting, HCPs in our study demonstrated poor estimation of cost accuracy patterns seen in studies done in more resource-abundant regions in Europe, Australasia and North America. [3,9,13,17-19]
Cost accuracy has remained poor in almost all studies assessing cost awareness, which may be due to poor education regarding the cost of healthcare consumables.  We hypothesise that a mathematical error consistent in most studies assessing cost awareness--the use of the percent deviation from the mean--contributes to this. Therefore, we employed the log deviation. Our results, however, demonstrate poor cost awareness, as has been observed consistently with previous studies. [3,9,13,17-19]
As this was a single-centre study, the study population may not be representative of HCPs in SA. The cost of expensive medical equipment or radiological investigations was not assessed because of logistical reasons. Various departments may have access to and thus familiarity with different equipment owing to the nature of their work; this study included a wide spectrum of HCPs. The cost of radiological investigations is not standard and also tends to differ, depending on the urgency of the request and the human resource and labour costs involved. We chose commonly used items and those that were unlikely to vary between departments in order to include various HCPs, avoiding bias with regard to occupation-related familiarity with specific equipment.
The interpretation of cost estimation accuracy differs among studies. Percentage deviation from true cost is often used to assess accuracy. If the cost estimation of an item or test is considered 'accurate' when the estimate is [+ or -] 25% of the true cost, the results will be errors of a small magnitude in true cost, but larger errors in terms of percentage. The latter are then highlighted as grossly deviant from the true cost. For example, an item of ZAR1 being overestimated as ZAR2, represents a ZAR1 difference from true cost, but a 100% deviation from true cost. However, the participant is still aware that the item falls into the 'cheap' category. This may not be economically relevant, as the item would still fall into the cheap category. We hypothesise that this is the reason that cheap items are often overestimated in cost awareness studies. Therefore, we used the more logical approach of log deviation. Although more mathematically correct, this is not in alignment with most (if not all) medical studies of cost awareness.
HCPs' estimations of cost were inaccurate. The majority indicated that they had not received adequate training with regard to cost and that they would like cost information to be readily available. This is significant, as HCPs may help to reduce healthcare expenditure. Increasing cost awareness may result in effective resource management. It is hoped that the findings of this study will help to inform cost awareness programmes and encourage the use of log deviation of true cost over estimated cost in the assessment of cost accuracy estimation.
Acknowledgements. Dr U Kirchner recommended using absolute log deviation in the assessment of cost accuracy estimations and assisted with the analysis and interpretation of the data. We would like to thank the departments of anaesthesia, general surgery, intensive care and obstetrics and gynaecology at CHBAH for participating in the study. We thank Prof. L R Mathivha for her assistance with reviewing the proposal, Dr S Vally for her assistance with the true cost of laboratory tests, and Drs E Buga and P Mogane for assisting with data collection.
Author contributions. GDN: conceived and designed the study, analysed and interpreted the data, and prepared the article for publication; ST: assisted with proposal development and ethics submission, investigated the true cost of the medications, distributed the survey, and collected and captured the data; and KJD: supervised the completion of the project and assisted with the preparation and revision of the article for publication.
Conflicts of interest. None.
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Accepted 1 June 2017.
G D Nethathe, (1,2) MB ChB, DA (SA), FCA (SA), MMed (Anaes), FANZCA, Cert Crit Care (SA), PGDip Health Science Education; S Tshukutsoane, (2) BCur Hons; K J Denny, (3) PhD, MBBS, BSc
(1) Department of Anaesthesia and Perioperative Medicine, Royal Brisbane and Women's Hospital, Brisbane; and Faculty of Medicine, University of Queensland, Brisbane, Australia
(2) Division of Critical Care, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
(3) Department of Intensive Care, Royal Brisbane and Women's Hospital, Brisbane, Australia
Corresponding author: G D Nethathe (firstname.lastname@example.org)
Caption: Fig. 1. Estimated cost accuracy by item, showing log of estimated cost over true cost and estimated cost accuracy by item. (IV = intravenous; FBC = full blood count; CRP = C-reactive protein; ET = endotracheal tube; PCT = procalcitonin; TPN = total parenteral nutrition; FFP = fresh-frozen plasma. Median values (dashed line); 50% percentile values (box outline); 90th percentile values (whiskers); and outlier values (open circles). Values >0 represent overestimations, and those <0 underestimations.)
Table 1. Demographics of surveyed healthcare practitioners (N=245) Demographics n (%) Gender Female 38 (15.5) Male 128 (52.2) Not stated 79 (32.2) Department Anaesthesia 23 (9.4) General surgery 78 (31.8) Intensive care 118 (48.1) Obstetrics and gynaecology 24 (9.8) Not stated 2 (0.8) Position in department Intern 23 (9.3) Medical officer 15 (6.1) Nurse assistant 8 (3.2) Professional nurse 114 (46.5) Registrar 26 (10.6) Specialist/consultant 31 (12.6) Staff nurse 24 (9.8) Other 3 (1.2) Not stated 1 (0.4) Involvement in private practice Yes 97 (39.6) No 143 (58.4) Not stated 5 (2.0) Table 2. Cost accuracy estimations per position in department, department, number of years in clinical practice, and involvement in private practice (N=245) * Accurate Underestimation (-0.2-0.2) ([less than or equal to] -0.2) Position in department, % Intern 11.01 29.27 Medical officer 10.00 26.81 Registrar 8.50 32.98 Specialist 9.54 30.80 Nurse assistant 4.20 37.81 Professional nurse 6.84 34.50 Staff nurse 4.87 34.67 Other 8.88 37.77 Department, % Anaesthesia 10.05 31.65 General surgery 7.85 33.94 Intensive care 7.13 33.58 Obstetrics and gynaecology 7.79 29.24 Clinical practice (years), n (%) 0-10 179 (8.04) 698 (31.37) 11-20 31 (7.52) 153 (37.13) [greater than or equal to] 21 38 (7.40) 171 (33.52) Private practice involvement, n (%) Yes 102 (7.15) 476 (33.38) No 173 (8.14) 698 (32.86) Overestimation Mean (SD) ([greater than or equal to] 0.2) Position in department, % Intern 59.71 0.73 (1.7) Medical officer 63.18 0.61 (1.7) Registrar 58.50 0.58 (1.6) Specialist 59.65 0.66 (1.6) Nurse assistant 57.98 0.41 (2.4) Professional nurse 58.65 0.55 (2.1) Staff nurse 60.45 0.78 (2.4) Other 53.33 0.03 (2) Department, % Anaesthesia 58.28 0.44 (1.5) General surgery 58.20 0.54 (2.1) Intensive care 59.28 0.63 (2.1) Obstetrics and gynaecology 62.95 0.79 (1.8) Clinical practice (years), n (%) 0-10 1 348 (60.58) 0.64 (1.9) 11-20 228 (55.33) 0.67 (1.9) [greater than or equal to] 21 303 (50.06) 0.51 (2.1) Private practice involvement, n (%) Yes 848 (59.47) 0.60 (2) No 1 253 (58.99) 0.59 (2) p-value Position in department, % Intern 0.167 Medical officer Registrar Specialist Nurse assistant Professional nurse Staff nurse Other Department, % Anaesthesia 0.078 General surgery Intensive care Obstetrics and gynaecology Clinical practice (years), n (%) 0-10 0.187 11-20 [greater than or equal to] 21 Private practice involvement, n (%) Yes 0.934 No SD = standard deviation. * The columns give the fraction of the population with a log estimate value between -0.2 and 0.2, <-0.2 and >0.2, respectively. Estimates were assessed as accurate if the log estimate value was between -0.2 and 0.2, underestimated if [less than or equal to] - 0.2, and overestimated if [greater than or equal to] 0.2.
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|Author:||Nethathe, G.D.; Tshukutsoane, S.; Denny, K.J.|
|Publication:||South African Medical Journal|
|Date:||Nov 1, 2017|
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