Software

RxRisk 2021 SAS Macro

Adelaide University

Widagdo, Imaina

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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25909/33044516.v1&rft.title=RxRisk 2021 SAS Macro&rft.identifier=10.25909/33044516.v1&rft.publisher=Adelaide University&rft.description=Administrative health claims data are increasingly accessible and play an important role in public health research. However, these data often lack detailed clinical information about patients’ health conditions and comorbidities. Accurately identifying comorbidities is important for epidemiological research, healthcare quality and safety, policy planning, and evaluation. The Rx-Risk Index uses prescription dispensing data to identify comorbidities and adjust for differences in health risk. This repository provides the SAS macro developed to apply the Rx-Risk Index to administrative prescription data, specifically the Pharmaceutical Benefits Scheme (PBS) data. &rft.creator=Widagdo, Imaina &rft.edition=1&rft_rights= https://creativecommons.org/licenses/by-nc-sa/4.0/&rft_subject=Epidemiology not elsewhere classified&rft_subject=Pharmacoepidemiology Australia&rft_subject=claims dataset&rft_subject=disease classification accuracy&rft_subject=Observational (nonexperimental) studies&rft.type=Computer Program&rft.language=English Access the software

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Full description

Administrative health claims data are increasingly accessible and play an important role in public health research. However, these data often lack detailed clinical information about patients’ health conditions and comorbidities. Accurately identifying comorbidities is important for epidemiological research, healthcare quality and safety, policy planning, and evaluation. The Rx-Risk Index uses prescription dispensing data to identify comorbidities and adjust for differences in health risk. This repository provides the SAS macro developed to apply the Rx-Risk Index to administrative prescription data, specifically the Pharmaceutical Benefits Scheme (PBS) data.

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Subjects

Epidemiology not elsewhere classified | Observational (nonexperimental) studies | Pharmacoepidemiology Australia | claims dataset | disease classification accuracy |

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Other Information

url : https://doi.org/10.2147/CIA.S494145 External Link

Identifiers

DOI : 10.25909/33044516.V1