Audit Commission (2010) Data remember: improving the quality of patient-based information in the NHS 2002. http://www.audit-commission.gov.uk/SiteCollectionDocuments/AuditCommissionReports/NationalStudies/dataremember.pdf May 2011, Date last accessed
Beckley IC, Nouraei R, Carter SS (2009) Payment by results: financial implications of clinical coding errors in urology. BJU Int 104(8):1043–1046
Article
Google Scholar
Berger RP, Parks S, Fromkin J, Rubin P, Pecora PJ (2015) Assessing the accuracy of the International Classification Of Diseases codes to identify abusive head trauma: a feasibility study. Injury Prev 21(e1):e133–e137
Article
Google Scholar
Burns EM, Rigby E, Mamidanna R, Bottle A, Aylin P, Ziprin P, Faiz OD (2011) Systematic review of discharge coding accuracy. J Publ Health 34(1):138–148
Article
Google Scholar
Butts MS, Williams DRR (1982) Accuracy of hospital activity analysis data. Br Med J (Clinical Research ed.) 285(6340):506
Article
Google Scholar
Campbell SE, Campbell MK, Grimshaw JM, Walker AE (2001) A systematic review of discharge coding accuracy. J Publ Health 23(3):205–211
Article
Google Scholar
Cimino JJ, Hripcsak G, Johnson SB, Clayton PD (1989). Designing an introspective, multipurpose, controlled medical vocabulary. In Proceedings/the… annual symposium on computer application [sic] in medical care. Symposium on computer applications in medical care, pp 513–518
Clark DE, Osler TM, Hahn DR (2010) ICDPIC: Stata module to provide methods for translating International Classification of Diseases (ninth revision) diagnosis codes into standard injury categories and/or scores. Statistical Software Components
Cleary R, Beard R, Coles J, Devlin B, Hopkins A, Schumacher D, Wickings I (1994) Comparative hospital databases: value for management and quality. Qual Health Car 3(1):3–10
Article
Google Scholar
Colville RJI, Laing JHE (2000) Coding plastic surgery operations: an audit of performance using OPCS-4. Br J Plast Surg 53(5):420–422
Article
Google Scholar
Davenport RJ, Dennis MS, Warlow CP (1996) The accuracy of Scottish morbidity record (SMR1) data for identifying hospitalised stroke patients. Health Bull 54(5):402–405
Google Scholar
Davis J, Mengersen K, Bennett S, Mazerolle L (2014) Viewing systematic reviews and meta-analysis in social research through different lenses. SpringerPlus 3(1):511
Article
Google Scholar
Dixon J, Sanderson C, Elliott P, Walls P, Jones J, Petticrew M (1998) Assessment of the reproducibility of clinical coding in routinely collected hospital activitydata: a study in two hospitals. J Publ Health 20(1):63–69
Article
Google Scholar
Dornan S, Murray FE, White G, McGilchrist MM, Evans JM, McDevitt DG, MacDonald TM (1995) An audit of the accuracy of upper gastrointestinal diagnoses in Scottish Morbidity Record 1 data in Tayside. Health Bull 53(5):274–279
Google Scholar
Drennan Y (1994). Data quality, patient classification systems, and audit: a recent study. In: Current perspectives in healthcare computing, Harrogate: BJHC Ltd., pp 54–60
Forbes C, Evans M, Hastings N, Peacock B (2011) Statistical distributions. Wiley, New York
Google Scholar
Gibson N, Bridgman SA (1998) A novel method for the assessment of the accuracy of diagnostic codes in general surgery. Ann R Coll Surg Engl 80(4):293
Google Scholar
Harley K, Jones C (1996) Quality of Scottish morbidity record (SMR) data. Health Bull 54(5):410–417
Google Scholar
Hasan M, Meara RJ, Bhowmick BK (1995) The quality of diagnostic coding in cerebrovascular. Int J Qual Health Care 7(4):407–410
Article
Google Scholar
Holder ME (2005) A modified Karnaugh map technique. IEEE Trans Educ 48(1):206–207
Article
Google Scholar
Kirkman MA, Mahattanakul W, Gregson BA, Mendelow AD (2009) The accuracy of hospital discharge coding for hemorrhagic stroke. Acta Neurol Belg 109(2):114–119
Google Scholar
Kohli HS, Knill-Jones RP (1992) How accurate are SMR1 (Scottish Morbidity Record 1) data? Health Bull 50(1):14–23
Google Scholar
McGonigal G, McQuade C, Thomas B (1992) Accuracy and completeness of Scottish mental hospital in-patient data. Health Bull 50(4):309–314
Google Scholar
Miller JF, Job D, Vassilev VK (2000) Principles in the evolutionary design of digital circuits—part I. Genet Program Evol Mach 1(1–2):7–35
Article
Google Scholar
Mitra I, Malik T, Homer JJ, Loughran S (2009) Audit of clinical coding of major head and neck operations. Ann R Coll Surg Engl 91(3):245
Article
Google Scholar
Murchison J, Barton JR, Ferguson A (1991) An analysis of cases incorrectly coded as inflammatory bowel disease in Scottish Hospital In-Patient Statistics (SHIPS). Scott Med J 36(5):136–138
Google Scholar
Nouraei SAR, O’Hanlon S, Butler CR, Hadovsky A, Donald E, Benjamin E, Sandhu GS (2009) A multidisciplinary audit of clinical coding accuracy in otolaryngology: financial, managerial and clinical governance considerations under payment-by-results. Clin Otolaryngol 34(1):43–51
Article
Google Scholar
Panayiotou B (1993) Coding of clinical diagnoses. Persevere with Körner system. Br Med J 306(6891):1541
Article
Google Scholar
Park RH, McCabe P, Russell RI (1992) Who should log SHIPS? The accuracy of Scottish Hospital Morbidity Data for Wilson’s disease. Health Bull 50(1):24–28
Google Scholar
Pears J, Alexander V, Alexander GF, Waugh NR (1992) Audit of the quality of hospital discharge data. Health Bull 50(5):356–361
Google Scholar
Reddy-Kolanu GR, Hogg RP (2009) Accuracy of clinical coding in ENT day surgery. Clin Otolaryngol 34(4):405–417
Article
Google Scholar
Rushdi AM (1985) Uncertainty analysis of fault-tree outputs. IEEE Transactions on Reliability R-34:458–462
Article
Google Scholar
Rushdi AM (1987) Improved variable-entered Karnaugh map procedures. Comput Electr Eng 13(1):41–52
Article
Google Scholar
Rushdi AM, Amashah MH (2011) Using variable-entered Karnaugh maps to produce compact parametric general solutions of Boolean equations. Int J Comput Math 88(15):3136–3149
Article
Google Scholar
Rushdi AM, Ba-Rukab OM (2005a) A doubly-stochastic fault-tree assessment of the probabilities of security breaches in computer systems. In: Proceedings of the Second Saudi science conference, Part Four: computer, mathematics, and statistics, Jeddah, Saudi Arabia, pp 1–17
Rushdi AM, Ba-Rukab OM (2005b) Fault-tree modelling of computer system security. Int J Comput Math 82(7):805–819
Article
Google Scholar
Rushdi AMA, Hassan AK (2015) Reliability of migration between habitat patches with heterogeneous ecological corridors. Ecol Model 304:1–10
Article
Google Scholar
Rushdi AMA, Hassan AK (2016a) An exposition of system reliability analysis with an ecological perspective. Ecol Ind 63:282–295
Article
Google Scholar
Rushdi AMA, Hassan AK (2016b) Quantification of Uncertainty in the Reliability of Migration between Habitat Patches (submitted)
Samy AK, Whyte B, MacBain G (1994) Abdominal aortic aneurysm in Scotland. Br J Surg 81(8):1104–1106
Article
Google Scholar
Sellar CMJK, Goldacre MJ, Hawton K (1990) Reliability of routine hospital data on poisoning as measures of deliberate self poisoning in adolescents. J Epidemiol Commun Health 44(4):313–315
Article
Google Scholar
Slee VN (1978) The International classification of diseases: ninth revision (ICD-9). Ann Intern Med 88(3):424–426
Article
Google Scholar
Smith SH, Kershaw C, Thomas IH, Botha JL (1991) PIS and DRGs: coding inaccuracies and their consequences for resource management. J Publ Health 13(1):40–41
Google Scholar
Steliarova-Foucher E, Stiller C, Lacour B, Kaatsch P (2005) International classification of childhood cancer. Cancer 103(7):1457–1467
Article
Google Scholar
World Health Organization (1992) International classification of disease and related health problems, 10th revision. World Health Organization, Geneva
World Health Organization (2004) International statistical classification of diseases and related health problems, vol 1. World Health Organization, Geneva
Google Scholar
Yeoh C, Davies H (1993) Clinical coding: completeness and accuracy when doctors take it on. Br Med J 306(6883):972
Article
Google Scholar
Zhang YS (2009) Determining all candidate keys based on Karnaugh map. In 2009 International conference on information management, innovation management and industrial engineering, pp 226–229