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GENERAL PRACTICE: Fiona D A Reid, Derek G Cook, and Azeem Majeed Explaining variation in hospital admission rates between general practices: cross sectional study BMJ 1999; 319: 98-103 [Abstract] [Full text]

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"HRG creep"

F J A Perlman, C J Watts   (20 July 1999)

Hospital admission rates may be misleading

Christopher JM Whitty   (23 July 1999)

Hospital Admission Rates and Resources Allocation

D L Child   (28 July 1999)

"HRG creep" 20 July 1999
F J A Perlman, 1. Appropriate clinical care physician 2. Director of Public Health Barking and Havering Health Authority, C J Watts Send response to journal: Re: "HRG creep"	Editor - With reference to the articles referring to the use of HES (Hospital Episode Statistic) data in this week’s BMJ1,2, we would like to inform you of some of the difficulties we have encountered in the use of this data in our locality. We have recently undertaken a study comparing rates of hospital admission for elective surgery for residents of this district with rates for residents of similar districts. This study used HES data grouped into HRGs (healthcare resource groups) for contracting purposes . This study attempted to identify procedures where rates of surgery for our residents were higher than those of the comparators. Amongst the procedures with higher rates, there were four procedures where the differences in rates were so large that we suspected that this might be due to discrepancies in the coding of procedures between trusts. Further enquiries revealed that our main provider was coding these procedures as a day case, whereas the vast majority of other trusts, including our other major local provider, appeared to be coding them as an outpatient procedure. The numbers of procedures identified is as follows: Procedure Number HRG Cost per day case of FCEs FCE from main provider Injection of haemorrhoids 151 F95 £390 Prostatic biopsy 285 L30 £243 Retinal coagulation 152 B05 £504 Hysteroscopy 726 M06 £455 Thus it can be seen that these day case procedures cost the health authority a total of £535,083. Discussions with this provider about the contracting arrangements revealed that some of these reclassifications had arisen for historical reasons where it had been advantageous to show a higher number of day cases, and that financially the charges for these procedures had been adjusted to ensure that these procedures would cost no more than they would had they been classified as an outpatient procedure. In subsequent years, however, this distinction was dropped and the full cost was charged. We have found no other examples in the literature of such problems in Britain, although in the USA, incorrect coding of DRGs (diagnosis related groups, the US equivalent) in the favour of health care providers, in their case for financial gain, is a recognised phenomenon. This has become known as ‘DRG creep’. Hsia, Krushat et al3 showed that from October 1984 to March 1985 there was an error rate of 20.8% in DRG coding. Unlike previous studies where errors had occurred randomly , this study showed that a statistically significant 61 percent of errors were in favour of hospitals, causing a 1.9% increase in their casemix (an index of complexity of the cases treated), leading to an increase in hospital reimbursement from Medicare of 308 million dollars. However, a follow up study by Hsia et al4, looking at accuracy of data coding between 1985 and 1988, showed that coding errors had declined to 14%, and that only 50.7% of these errors (a statistically non-significant figure) were in favour of hospitals. Goldfarb and Coffey5 analysed changes in casemix during the early years of the Medicare PPS (prospective payment system) using data from 1980-86. They used statistical techniques, including regression analysis, in order to assess how much of the increase in casemix was as a result of the change in payment system, and how much was due to underlying changes in medical practice. They estimated that half of the change was due to each, but that the effect of coding was starting to decline by 1986. This would concur with the findings in the second paper of Hsia4. This paper cites the influence of stringent Medicare peer review organisations as the main influence in reducing the rise in casemix. A Medline search shows that little since then has been published in relation to this issue. However, searching the Internet reveals that careful coding may still be alive and well. Using the ‘Alta Vista’ search engine, the terms ‘DRGs’ and ‘coding accuracy’ revealed a number of commercial companies in the USA offering services and software to improve hospitals’ accuracy of coding with the explicit aim of increasing hospital income. Conversely another company offered software to reduce the expenditure of healthcare purchasers, also by examining coding. We wonder if there are any other examples of major HRG coding discrepancies in Britain, which favour the interests of NHS trusts, whether these interests are administrative or financial, and whether our findings could reflect altered behaviour of trusts in response to the purchaser-provider arrangements of the changed NHS. In addition it is clear that such coding discrepancies affect the use of this data for comparisons of hospital admission rates. We wonder whether there are any examples in this country of miscoding for explicit financial reward, and whether ‘HRG creep’ could become a recognised entity in the UK. Yours faithfully Dr F.J.A. Perlman, Project Facilitator Dr C.J. Watts, Director of Public Health Public Health Department Barking and Havering Health Authority, The Clock House, East Street, Barking. IG11 8EY References 1. Giuffrida A, Gravelle H, Roland M. Measuring quality of care with routine data: avoiding confusion between performance indicators and health outcomes. BMJ, 1999; 319:94-98 2. Reid FDA, Cook DG, Majeed A. Explaining variation in hospital admission rates between hospital practices: cross sectional study. BMJ, 1999; 319:98 -103 3. Hsia DC, Krushat WM et al. Accuracy of diagnostic coding for Medicare patients under the prospective payment system. N Eng J Med, 1998; 318(6): 352-5 4. Hsia DC, Ahern CA et al. Medicare reimbursement accuracy under the prospective payment system, 1985-1988. JAMA, 1992; 268(7): 896-9 5. Goldfarb MG: Coffey RM. Change in the Medicare case-mix index in the 1980s and the effect of the prospective payment system. Health Services Research, 1992; 27(3): 385-415
Hospital admission rates may be misleading 23 July 1999
Christopher JM Whitty Send response to journal: Re: Hospital admission rates may be misleading	Editor- Rates of general practitioner referrals to hospital outpatients have been extensively studied, but emergency referrals, which are potentially far more disruptive to patients, as well as being very expensive, have not. Reid et al in their study published 10 July (1) address this issue indirectly by studying hospital admissions in a large well designed study. They acknowledge, and the accompanying editorial (2) also highlights, that admission rates do not necessarily reflect referral rates. This is not just a theoretical point. In a pilot prospective study of 760 emergency referrals to Northwick Park Hospital, London, in 1993-4 there was a very wide variation in referral patterns. The highest referring practice, which referred over 4 times the median number, had under a quarter of all referrals admitted, the rest being sent home after assessment. The average practice had two-thirds of their referrals admitted. This does not necessarily mean that any referrals were inappropriate, but if emergency admission rates had been studied the difference in referral rates would have appeared much smaller than it was. In this small sample 20% of all emergency referrals made to the hospital were made by 10 GPs, out of over 200 GPs in the hospital catchment area. Trying to determine emergency referral rates accurately is fraught with methodological problems, but wide differences in admissions seen in studies of emergency admissions may well be a significant underestimate of the differences in true rates of referral. Yours faithfully Christopher JM Whitty Lecturer Department of Medicine, College of Medicine, University of Malawi, Private Bag 360, Chichiri, Blantyre 3, Malawi. 1) Reid FDA, Cook DG, Majeed A. Explaining variation in hospital admission rates between general practices: cross sectional study. BMJ 1999; 319: 98-103 2) Jankowski R. What do hospital admission rates say about primary care? BMJ 1999; 319: 67-8.
Hospital Admission Rates and Resources Allocation 28 July 1999
D L Child, Principal Cape Hill Medical Centre Send response to journal: Re: Hospital Admission Rates and Resources Allocation	Fiona Reid et al’s observation that variation in hospital admission rates between general practices is related to patients’ socio-economic factors rather than practice characteristics comes as little surprise since the study was conducted across an entire health authority with considerable social diversity. Likewise the lack of correlation between proxies of quality in practices – cervical screening uptake rates etc – and hospital admissions is easily explicable in that the former directly enhanced the doctors earnings while referral and admission rates reflect in part the burden of clinical load primary care doctors are willing to accept. With the advent of Primary Care Groups evidence is emerging that individual practices within a locality may vary greatly in both the baseline budget they enjoy for practice staff and the support they receive from community based staff. Such variation probably reflects the historic enterprise of individual practices in maximising opportunities to improve patient care both through General Medical Services monies and fund-holding budgets. It follows, therefore, that to evaluate performance indicators it might prove more productive to study populations with uniform socio- economic circumstances and the practices that serve them. Once the population is standardised then it should prove possible to examine suitably selected practice characteristics, eg baseline staff budgets and community staff, in relation to referral rates and admission rates. For the purposes of resource allocation within individual PCGs this work needs to be urgently undertaken.