Estimating the gains of early detection of hypertension over the marginal patient.
Paul Andres Rodriguez-LesmesPublished in: PloS one (2021)
This study estimated the potential impact of early diagnosis programs on health outcomes in England. Specifically, if advising individuals to visit their family doctor due to a suspected case of mild hypertension would result in (i) an increase in the diagnosis and treatment of high blood pressure; (ii) an improved lifestyle reflected in objective measures such as the body-mass-index and blood pressure levels; (iii) a reduced probability of the onset of other cardiovascular diseases, such as diabetes. To address potential selection bias in screening, a feature of the English Longitudinal Study of Ageing is exploited, motivating a regression discontinuity design. If respondents' blood pressure measurements are above a standard clinical threshold, they are advised to visit their family doctor to confirm hypertension. Two years after the protocol, there is evidence of an increase in diagnosis (5.7 pp, p-val = 0.06) and medication use (6 pp, p-val = 0.007) for treating the condition. However, four years after the protocol, the difference in diagnosis and medication disappeared (4 pp, p-val = 0.384; 3.4 pp, p-val = 0.261). Moreover, there are no differences on observed blood pressure levels (systolic 0.026 mmHg, p-val = 0.815; diastolic -0.336 mmHg, p-val = 0.765), or Body-Mass-Index ((0.771, p-val = 0.154)). There are also no differences on diagnosis of diabetes (1.7 pp, p-val = 0.343) or heart related conditions (3.6 pp, p-value = 0.161). In conclusion, the nudge produces an earlier diagnosis of around two years, but there are no perceivable gains in health outcomes after four years.
Keyphrases
- blood pressure
- hypertensive patients
- cardiovascular disease
- heart rate
- body mass index
- type diabetes
- healthcare
- randomized controlled trial
- public health
- blood glucose
- physical activity
- heart failure
- mental health
- machine learning
- left ventricular
- metabolic syndrome
- glycemic control
- pulmonary embolism
- climate change
- deep learning
- risk assessment
- insulin resistance
- case report
- human health
- adipose tissue
- social media
- ejection fraction