We developed and validated a computer case definition for sudden cardiac death for use in automated databases linked with death certificates. Our motivation was to improve the efficiency and quality of studies of medications and sudden cardiac death by reducing the time and expense required for medical record review and avoiding bias due to the exclusion of cases for whom medical records are either unavailable or non-informative. In the development sample, the definition had a positive predictive value of 86.0%; in the validation sample the positive predictive value was 86.8%. This suggests the computer case definition will be useful for studies of medications and sudden cardiac death.
Our study positive predictive value is higher than that from five previous studies that assessed the performance of death-certificate based definitions of sudden cardiac death,22–26
which reported values of 19%,22
We believe these differences resulted from three separate factors: the computer case definition for sudden cardiac death, the population studied, and the gold-standard definition used.
The previous studies used only the death certificates to identify potential sudden cardiac deaths. In contrast, we utilized three distinct sources of information: the death certificates, a state hospital discharge database, and records of medical encounters from the Medicaid program. The additional Tennessee data sources were essential for exclusion of deaths unlikely to meet the case definition. For example, in the Minnesota study, of 1409 deaths considered for medical record review, 285 (20.2%) actually occurred following hospital admission,22
despite a death certificate indicating out-of-hospital death. In that study, these deaths were false positives, whereas, in our study, such deaths would have been excluded.
Our study also was selective with regard to the specific cause-of-death diagnostic codes considered. For example, it did not include underlying cause of death codes for heart failure or stroke, which would have been included in some of the other definitions.
We excluded persons 75 years of age or older and nursing home residents because our experience indicated that the positive predictive value would be lower for these populations. This exclusion also may have increased the predictive value of the Tennessee definition relative to that of the other studies. This exclusion is an important limitation as the patient groups account for a substantial fraction of sudden cardiac deaths. If our definition is to be used in these populations, further validation studies would be necessary.
Our definition included both probable and possible cases of sudden cardiac death. Some of the prior studies were restricted to probable sudden cardiac deaths;22
had we done this the positive predictive value would have been 54%.
A limitation of the validation study was that 45% of deaths in the sample (142/316) were not adjudicated, primarily for two reasons. First, for 74 deaths (23%) the augmented Medicaid files did not have either autopsy reports or records for the year preceding death from sources we have found to be most informative and accessible: hospital emergency departments, hospital-based clinics, and emergency medical services. This proportion decreased with calendar year, with 34% of deaths not adjudicated for this reason prior to 2000 as opposed to 17% subsequently. However, the PPV actually increased slightly for the later period (85% prior to 2000 versus 88% subsequently), suggesting this factor had little effect on our findings. Second, the records retrieved for 63 deaths (20%) did not have sufficient information for adjudication, primarily because the record did not contain observer reports describing the arrest or the patient's prior health. Further studies with higher proportions of adjudicated deaths would be useful, although these might need to go beyond medical record review and either seek to interview decedents' contacts or use prospective methods.23
The validation sample only included deaths that met the computer case definition and thus cannot be used to estimate sensitivity. However, in the development sample, we reviewed a broader range of deaths, following a strategy similar to that in the Minnesota study.22
For that sample, we found that the computer case definition misclassified 25% of confirmed sudden cardiac deaths. This suggests that the sensitivity is less than 75%, given that a review of all deaths (for example, including those coded as due to cancer, excluded from several of the studies22
) would identify even more confirmed cases. Thus, the computer case definition may be more useful for etiologic investigations than for studies of the absolute incidence of sudden cardiac death.
Many sudden cardiac deaths were identified from underlying cause of death codes for acute myocardial infarctions and coronary atherosclerosis. Standard definitions of sudden cardiac death19
include myocardial infarctions, so long as they are rapidly fatal and thus meet the "sudden" criteria. In susceptible patients, an ischemic event such as a myocardial infarction is often, but not always the trigger of ventricular tachyarrhthmias – the most common cause of sudden cardiac death.2
If the patient has a genetic predisposition or is taking a proarrhythmic drug, an infarction may be more likely provoke a lethal arrhythmia than in a comparable patient without these factors. When cardiac arrest occurs outside of the hospital and the patient dies quickly, there often is very limited medical investigation of the death. Thus, the appropriate codes on the death certificate are those that indicate a death related to coronary artery disease, such as myocardial infarction or atherosclerosis.
Both the development and validation samples for the computer case definition consisted of Tennessee Medicaid enrollees. Thus, its performance may be different in other populations. However, performance of computer case definitions has been broadly similar in Medicaid and non-Medicaid populations for other diseases, including gastroduodenal ulcers,27
and myocardial infarction.29
An important limitation of the computer case definition is that approximately 13% of cases identified will be false positives that could have been excluded by medical record review. If this misclassification is non-differential, it will bias to the null, thus modestly reducing the power of studies to detect medication effects. Of greater concern is differential misclassification according to drug exposure status, which would bias medication studies. However, our findings provide some evidence that this does not occur, as the positive predictive value in the validation sample was the same for both baseline users and nonusers of antipsychotics.
In conclusion, we developed and validated a computer case definition for sudden cardiac death for use in automated databases linked with death certificates. The definition had a positive predictive value of 86.8% in the validation sample, which should make it a useful tool for pharmacoepidemiologists.
There is considerable interest in effects of medications on the risk of sudden cardiac death. Automated databases with prescription records and linked to computerized death certificates have potential for such studies. However, medical record review for possible sudden deaths poses formidable logistic difficulties. We developed and validated by medical record review a sudden cardiac death computer case definition in the linked Tennessee Medicaid database. The positive predictive value was 87%, making this definition a useful tool for pharmacoepidemiologists.