Best-Link Matching of Scottish Health Data Sets

1998 ◽  
Vol 37 (01) ◽  
pp. 64-68 ◽  
Author(s):  
M. M. Douglas ◽  
D. Gardner ◽  
D. Hucker ◽  
S. W. Kendrick
Keyword(s):  
Community Health ◽  
Health Data ◽  
Data Sets ◽  
Health Index ◽  
Probability Matching ◽  
Central Register ◽  
National Patient ◽  
Degree Of Confidence ◽  
Sufficient Degree ◽  
Matching Techniques

Abstract:Methods are described used to link the Community Health Index and the National Health Service Central Register (NHSCR) in Scotland to provide a basis for a national patient index. The linkage used a combination of deterministic and probability matching techniques. A best-link principle was used by which each Community Health Index record was allowed to link only to the NHSCR record with which it achieved the highest match weight. This strategy, applied in the context of two files which each covered virtually the entire population of Scotland, increased the accuracy of linkage approximately a thousand-fold compared with the likely results of a less structured probability matching approach. By this means, 98.8% of linkable records were linked automatically with a sufficient degree of confidence for administrative purposes.

The Community Health Index-how accurate is it?

1988 ◽  
Vol 10 (4) ◽  
pp. 327-330 ◽  
Author(s):  
M. A. Roworth ◽  
I. G. Jones
Keyword(s):  
Community Health ◽  
Health Index

scholarly journals COVID-19 Growth Rate Decreases with Social Capital

2020 ◽  
Author(s):  
Lav R. Varshney ◽  
Richard Socher
Keyword(s):  
United States ◽  
Social Capital ◽  
Growth Rate ◽  
Community Health ◽  
Human Mobility ◽  
County Level ◽  
Health Index ◽  
Negatively Associated ◽  
Social Distancing ◽  
Health Indices

AbstractBackgroundSocial capital has been associated with many public health variables including mortality, obesity, diabetes, and sexually-transmitted disease rates. However, the relationship of social capital to the spread of infectious disease like COVID-19 is lacking. The COVID-19 pandemic presents an unprecedented threat to global health and economy, for which control strategies have relied on aggressive social distancing. However, an understanding of how social capital is related to changes in human mobility patterns for adherence to social distancing is lacking.ObjectiveThis study examines the association between state- and county-level social capital indices and community health indices in the United States, and the growth rate of COVID-19 cases. It also examines changes in human mobility.MethodsUsing publicly available state- and county-specific time series data for COVID-19 cases from March 13 to March 31, we used exponential fits to determine growth rate. We obtained publicly available mobility change data, originally measured from GPS-enabled mobile devices. The design was then state- and county-level correlation analysis with social capital and community health indices from the Social Capital Project (United States Senate).ResultsIn bivariate linear correlation analyses, we find social capital and community health indices were negatively associated with COVID-19 growth rates at both the state and county levels. The correlation was strongest at the county level for the community health index: a one-unit increase in the county community health index was associated with a decrease in the COVID-19 growth rate exponent by 0.045. In further bivariate correlation analyses, we find that social capital indices were negatively associated with retail/recreation movement and positively associated with residential movement. That is, an increase in social capital is correlated with slower COVID-19 infection spread and more adherence to social distancing protocols.ConclusionOur results indicate the potential benefit of incorporating social capital concepts in planning policies to control the spread of COVID-19, e.g. different social distancing requirements in different communities. The results also indicate a need for further research into this potentially causal relationship, including examining interventions to increase social capital, community health, and institutional health.

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