BACKGROUND: Calculating disease prevalence requires both a numerator (number of persons with a disease) and a matching denominator (the 'population at risk' being studied). Determining primary care practice denominators is challenging. OBJECTIVE: To develop and test a method to calculate primary care practice denominators. METHODS: We compared a 'corrected yearly contact group', or practice population, with the number of patients enrolled with practices. The yearly contact group was the set of patients with a visit noted in the electronic medical records during the past year. The correction factor was the proportion of patients that reported contacting their physician in the past year. Eighty-one physicians from Toronto and Kingston, Ontario, provided data. The main outcome measure was the ratio of practice population to the number of enrolled patients. Other measures included the change in ratio over 2 years, differences between locations, and differences by provider, practice and patient characteristics. RESULTS: The ratio of practice population to enrolled patients was 1.03 in 2010 (95% confidence interval 1.00 to 1.05) and 1.03 in 2011 (95% confidence interval 1.00 to 1.05). There was no change in the ratio over time. Ratios by location, provider or practice characteristics differed by less than 10%. There was a slight under-estimation of practice population for younger male patients and over-estimation for female patients. CONCLUSION: This method provided a denominator that was reasonably similar to the enrolled population and was stable over time and by location, provider and practice characteristics. In regions without patient enrollment, this may provide an estimate of practice denominators.
BACKGROUND: Calculating disease prevalence requires both a numerator (number of persons with a disease) and a matching denominator (the 'population at risk' being studied). Determining primary care practice denominators is challenging. OBJECTIVE: To develop and test a method to calculate primary care practice denominators. METHODS: We compared a 'corrected yearly contact group', or practice population, with the number of patients enrolled with practices. The yearly contact group was the set of patients with a visit noted in the electronic medical records during the past year. The correction factor was the proportion of patients that reported contacting their physician in the past year. Eighty-one physicians from Toronto and Kingston, Ontario, provided data. The main outcome measure was the ratio of practice population to the number of enrolled patients. Other measures included the change in ratio over 2 years, differences between locations, and differences by provider, practice and patient characteristics. RESULTS: The ratio of practice population to enrolled patients was 1.03 in 2010 (95% confidence interval 1.00 to 1.05) and 1.03 in 2011 (95% confidence interval 1.00 to 1.05). There was no change in the ratio over time. Ratios by location, provider or practice characteristics differed by less than 10%. There was a slight under-estimation of practice population for younger male patients and over-estimation for female patients. CONCLUSION: This method provided a denominator that was reasonably similar to the enrolled population and was stable over time and by location, provider and practice characteristics. In regions without patient enrollment, this may provide an estimate of practice denominators.
Entities:
Keywords:
Electronic health records; epidemiologic methods; health care evaluation mechanisms; morbidity prevalence; primary health care; sentinel surveillance.
Authors: Michael E Green; Nandini Natajaran; Denis E O'Donnell; Tyler Williamson; Jyoti Kotecha; Shahriar Khan; Andrew Cave Journal: CMAJ Open Date: 2015-01-13
Authors: Antônio Thomaz Gonzaga Matta-Machado; Ângela Maria L Dayrell de Lima; Daisy Maria Xavier de Abreu; Lucas Lobato Araújo; Délcio Fonseca Sobrinho; Érica Araújo Silva Lopes; Gabriel Henrique Silva Teixeira; Alaneir de Fátima Dos Santos Journal: J Ambul Care Manage Date: 2017 Apr/Jun
Authors: S Garies; M Cummings; B Forst; K McBrien; B Soos; M Taylor; N Drummond; D Manca; K Duerksen; H Quan; T Williamson Journal: Int J Popul Data Sci Date: 2019-07-29