This page provides a place for investigators to share code, syntax, software and other tools that they have used in their multiple chronic conditions (MCC) research to help other investigators working on MCC research. Are you willing to share programming code or other resources that may be useful for other MCC investigators? If so, please let us know at 734-647-2200 or email@example.com
Chronic Condition Classification
The chronic condition classification spreadsheet (.xls 101K) was developed by Dr. Wenke Hwang and colleagues in 2001 (see: Hwang W, Weller W, Ireys H, Anderson G. Out-of-Pocket Medical Spending For Care Of Chronic Conditions. Health Affairs, 20, no6 (2001):267-278. DOI: 10.1377/hltaff.20.6.267), and then updated in 2009 (Paez KA, Zhao L, and Hwang W. Rising Out-Of-Pocket Spending For Chronic Conditions: A Ten-Year Trend. Health Affairs, 28, no.1 (2009):15-25. DOI: 10.1377/hlthaff.28.1.15).
To develop this chronic condition classification, two panels of physicians (one with five internists and another with five pediatricians) were convened to review the ICD-9 codes included in the MEPS data, and determine if each fit a definition of a chronic condition (defined as a condition that that "lasted or was expected to last twelve or more months and resulted in functional limitations and/or the need for ongoing medical care").
The scores (from 5 to -5) indicate the extent of the agreement across panel members, with a score of 5 indicating that all five physicians rated the diagnosis as "chronic", and a score of -5 indicating that all five panelists rated a diagnosis as "not chronic". If there is disagreement, the score indicates the extent of the agreement/disagreement (for example, if three physicians say "yes" (+3), one says "no' (-1), and one says "not sure" (0), the final score is 2). The panels could not resolve a few conditions, and "DC" (dental consult) and "PC" (pediatric consult) indicate these cases.
CMS' ICD-9-CM to and from ICD-10-CM and ICD-10-PCS Crosswalk or General Equivalence Mappings
The National Bureau of Economic Research (NBER) has provided information about the Centers for Medicare & Medicaid Services (CMS) ICD-9-CM to and from ICD-10-CM and ICD-10-PCS General Equivalence Mappings, which "makes converting from ICD-9-CM to or from ICD-10-CM and ICD-10-PCS easier." On the site, NBER also provides "processed versions of the files and combined the CM and PCS to make the files easier to use."
- This SQL code (.txt) was several years ago (~7). During the validation process we discovered some local coding practices that did not conform to the Deyo et al. recommendations. Also included is an Excel spreadsheet that we used as the lookup table to score our codes. Comments represent local practices. (Source: Bill Trick)
- This SAS code (.txt) is older code (~6 years?) and was shared by another institution; we were pleased to see good concordance with our SQL code. (Source: Bill Trick)
Health Outcomes of Interest (HOI)
Observational Medical Outcomes Partnership's open-source library of ten Health Outcomes of Interest (HOI) definitions for use in observational studies.
Health-Related Quality of Life
Centers for Disease Control and Prevention's syntax to recode and/or create Health-Related Quality of Life variables.
Healthcare Costs and Utilization Project (HCUP) Tools
Healthcare Cost and Utilization Project's (HCUP) tools and software for identifying, tracking, analyzing, and comparing statistics on hospital and emergency care.
Grid-Enabled Measures (GEM)
Grid-Enabled Measures (GEM) is a web-based database using a wiki platform that provides researchers and program evaluators with standard measures, tools, and databases. If researchers use the same measures, then eventually they can share data across projects. The wiki platform enables collective improvements and shared learning. Examples of just a few of the many topics for which GEM offers measures are:
- Perceived quality of care
- Social support
- Organizational readiness for change
- Effective communication
- Health literacy/numeracy
GEM also organizes its measures into content areas such as cancer, smoking/tobacco, obesity, and mental health. At the GEM website, users can find content areas and topics, how the topic is defined and where it came from (its theoretical foundation), and download different measures for each topic. Characteristics of the measures (e.g., definition, intended population, reliability, validity) are also available. Users can add to the website, and provide feedback and rate the measures.