Coding errors in an analysis of the impact of pay-for-performance on the care for long-term cardiovascular disease: a case study.
OBJECTIVE
There is no standard method of publishing the code ranges in research using routine data. We report how code selection affects the reported prevalence and precision of results.


METHODS
We compared code ranges used to report the impact of pay-for-performance (P4P), with those specified in the P4P scheme, and those used by our informatics team to identify cases. We estimated the positive predictive values (PPV) of people with chronic conditions who were included in the study population, and compared the prevalence and blood pressure (BP) of people with hypertension (HT).


METHODS
Routinely collected primary care data from the quality improvement in chronic kidney disease (QICKD-ISRCTN56023731) trial.


METHODS
The case study population represented roughly 85% of those in the HT P4P group (PPV = 0.842; 95%CI = 0.840-0.844; p < 0.001). We also found differences in the prevalence of stroke (PPV = 0.694; 95%CI = 0.687- 0.700) and coronary heart disease (PPV = 0.166; 95%CI = 0.162-0.170), where the paper restricted itself to myocardial infarction codes.


RESULTS
We found that the long-term cardiovascular conditions and codes selected for these conditions were inconsistent with those in P4P or the QICKD trial. The prevalence of HT based on the case study codes was 10.3%, compared with 11.8% using the P4P codes; the mean BP was 138.3 mmHg (standard deviation (SD) 15.84 mmHg)/79.4 mmHg (SD 10.3 mmHg) and 137.3 mmHg (SD 15.31)/79.1 mmHg (SD 9.93 mmHg) for the case study and P4P populations, respectively (p < 0.001).


CONCLUSIONS
The case study lacked precision, and excluded cases had a lower BP. Publishing code ranges made this comparison possible and should be mandated for publications based on routine data.
Clinical Informatics and Health Outcomes Research Group, Department of Health Care Management and Policy, University of Surrey, Guildford GU2 7XH, UK.
Simon
S
de Lusignan
Clinical Informatics and Health Outcomes Research Group, Department of Health Care Management and Policy, University of Surrey, Guildford GU2 7XH, UK.
Benjamin
B
Sun
Melbourne East General Practice Network, Suite 13, Level 1, 317?321, Whitehorse Road, Nunawading VIC 3131, Australia.
Christopher
C
Pearce
Department of Renal Medicine, East Kent Hospitals University NHS Foundation Trust, Canterbury CT1 3NG, UK.
Christopher
C
Farmer
Department of Renal Medicine, East Kent Hospitals University NHS Foundation Trust, Canterbury CT1 3NG, UK.
Paul
P
Steven
Clinical Informatics and Health Outcomes Research Group, Department of Health Care Management and Policy, University of Surrey, Guildford GU2 7XH, UK.
Simon
S
Jones
D002318:Cardiovascular Diseases / Q000145:classification* / Q000453:epidemiology; D059019:Clinical Coding / Q000592:standards*; D057286:Electronic Health Records; D006801:Humans; D006973:Hypertension / Q000145:classification / Q000453:epidemiology; D019982:Organizational Case Studies; D015995:Prevalence; D058996:Quality Improvement; D011787:Quality of Health Care; D012052:Reimbursement, Incentive; D012107:Research Design