Imputation Methodologies. The predictive mean matching imputation method was used to impute missing expenditures. This procedure uses regression models (based on events with completely reported expenditure data) to predict total expenses for each event. Then, for each event with missing payment information, a donor event with the closest predicted payment with the same pattern of expected payment sources as the event with missing payment was used to impute the missing payment value. The imputations for the flat fee events were carried out separately from the simple events. The weighted sequential hot-deck procedure was used to impute the missing total charges. This procedure uses survey data from respondents to replace missing data while taking into account the persons’ weighted distribution in the imputation process.
Imputation Methodologies. The predictive mean matching imputation method was used to impute missing expenditures. This procedure uses regression models (based on events with completely reported expenditure data) to predict total expenses for each event. Then, for each event with missing payment information, a donor event with the closest predicted payment with the same pattern of expected payment sources as the event with missing payment was used to impute the missing payment value. The weighted sequential hot-deck procedure was used to impute the missing total charges. This procedure uses survey data from respondents to replace missing data while taking into account the persons’ weighted distribution in the imputation process.
Imputation Methodologies. The predictive mean matching imputation method was used to impute missing expenditures. This procedure uses regression models (based on events with completely reported expenditure data) to predict total expenses for each event. Then, for each event with missing payment information, a donor event with the closest predicted payment with the same pattern of expected payment sources as the event with missing payment was used to impute the missing payment value. The weighted sequential hot-deck procedure was used to impute the missing total charges. This procedure uses survey data from respondents to replace missing data while taking into account the persons’ weighted distribution in the imputation process. The imputations for the flat fee events were carried out separately from the simple events. Expenditures for services provided by separately billing doctors in hospital settings were also edited and imputed. These expenditures are shown separately from hospital facility charges for hospital inpatient, outpatient, and emergency room care.
Imputation Methodologies. The predictive mean matching imputation method was used to impute missing expenditures. This procedure uses regression models (based on events with completely reported expenditure data) to predict total expenses for each event. Then, for each event with missing payment information, a donor event with the closest predicted payment with the same pattern of expected payment sources as the event with missing payment was used to impute the missing payment value. Within each event type file, separate imputations were performed for flat fee and simple events. Separate imputations were performed for visits to physicians (where MPCELIG=1) and visits to non-physician providers (where MPCELIG=2). After the imputations were finished, visits to physician and non-physician providers were combined into a single medical provider file. The weighted sequential hot-deck procedure was used to impute the missing total charges. This procedure uses survey data from respondents to replace missing data while taking into account the persons’ weighted distribution in the imputation process.
Imputation Methodologies. For events in this file that were eligible for the MEPS-MPC (i.e. home health agency events where MPCELIG = 1), a predictive mean matching imputation method was used to impute missing expenditures. This procedure uses regression models (based on events with completely reported expenditure data) to predict total expenses for each event. Then, for each event with missing payment information, a donor event with the closest predicted payment with the same pattern of expected payment sources as the event with missing payment was used to impute the missing payment value. For events in this file that were not eligible for the MEPS-MPC (i.e. home health paid independent events where MPCELIG = 2), a weighted sequential hot-deck procedure was used to impute missing expenditures. This procedure uses survey data from respondents to replace missing data while taking into account the persons’ weighted distribution in the imputation process. Classification variables vary by type of provider in the hot-deck imputations, but total charge (when available) and insurance coverage are key variables in all of the imputations. The weighted sequential hot-deck procedure was also used to impute the missing total charges for both home health agency events and home health paid independent events. After the imputations were finished, the two categories of home care also were combined into a single home health file.
Imputation Methodologies. For events in this file that were eligible for the MEPS-MPC (i.e. physician office visits where MPCELIG=1), a predictive mean matching imputation method was used to impute missing expenditures. This procedure uses regression models (based on events with completely reported expenditure data) to predict total expenses for each event. Then, for each event with missing payment information, a donor event with the closest predicted payment with the same pattern of expected payment sources as the event with missing payment was used to impute the missing payment value. For events in this file that were not eligible for the MEPS-MPC (i.e. non- physician visits where MPCELIG=2), a weighted sequential hot-deck procedure was used to impute missing expenditures. This procedure uses survey data from respondents to replace missing data while taking into account the persons’ weighted distribution in the imputation process. Classification variables vary by type of provider in the hot-deck imputations, but total charge (when available) and insurance coverage are key variables in all of the imputations. Separate imputations were performed for flat fee and simple events. The weighted sequential hot-deck procedure was also used to impute the total missing charges. After the imputations were completed, visits to physician and non-physician providers were combined into this office- based medical provider visits file.
