Research visual

Health Research

Diabetes Complications Severity Index (DCSI) – update and ICD-10 translation

Glasheen WP,  Renda A, Dong Y. Diabetes Complications Severity Index (DCSI) – update and ICD-10 translation. J Diabetes Complications. 2017;31(6):1007-1013.

http://authors.elsevier.com/sd/article/S105687271631042X

A predictive model for identifying individuals with diabetes at high risk of progression using Diabetes Complication Severity Index (DCSI)

Fan J, Dong Y, Chiguluri V, Glasheen W, Renda A, Prewitt T, Gopal V. A predictive model for identifying individuals with diabetes at high risk of progression using Diabetes Complication Severity Index. Diabetes 2016 Jun; 65(Supplement 1): A602.

Beyond the limits of predictive models: responding to patients’ self-identification of residual readmission risk

Ferries E, Hall B. Beyond the limits of predictive models: responding to patients’ self-identification of residual readmission risk. Poster presentation at: Society for Judgment and Decision Making Annual Meeting. November 19, 2016. Boston, MA.

http://apps.humana.com/marketing/documents.asp?file=3070340

Leveraging predictive modeling to improve the participant identification process for transition to dialysis support programs

Cockrell M, Dong Y, Hines H, Haugh G, Gopal V, Beveridge R, Prewitt T. Leveraging predictive modeling to improve the participant identification process for transition to dialysis support programs. Journal of the American Society of Nephrology. 2015(26):926A.

Validation of febrile seizures identified in the mini-sentinel post-licensure rapid immunization safety monitoring (PRISM) system

Kawai AT, Martin D, McMahill-Walraven CN, et al. Validation of febrile seizures identified in the mini-sentinel post-licensure rapid immunization safety monitoring (PRISM) system. Poster presentation at: Infectious Disease Week. October 8-14, 2014; Philadelphia, PA.

http://apps.humana.com/marketing/documents.asp?file=2574559

Understanding predictors of opioid abuse: predictive model development and validation

Dufour R, Mardekian J, Pasquale MK, et al. Understanding predictors of opioid abuse: predictive model development and validation. Poster presentation at: Academy of Managed Care Pharmacy Nexus 2013. October 15-18, 2013; San Antonio, TX.

http://apps.humana.com/marketing/documents.asp?file=2574533

The Humana database - a data source for pharmacoepidemiologic research

Michels SL, Uribe C. The Humana database - a data source for pharmacoepidemiologic research. Poster presentation at: 28th Annual International Conference for Pharmacoepidemiology and Therapeutic Risk Management. August 23-26, 2012; Barcelona, Spain.

http://apps.humana.com/marketing/documents.asp?file=2574520

Structured advanced care planning facilitated by case managers

Rodkey W, Morrison J, Rackow E. Structured advanced care planning facilitated by case managers. Poster presentation at: Palliative Care in Oncology Symposium. October 24-25, 2014; Boston, MA.

http://apps.humana.com/marketing/documents.asp?file=2645227

Segmentation of a Medicare Advantage population using the Diabetes Complications Severity Index (DCSI)

Chiguluri V, Cusano D, Glasheen W, et al. Segmentation of a Medicare Advantage population using the Diabetes Complications Severity Index (DCSI). Poster presentation at: American Public Health Association 142nd Annual Meeting and Exposition. November 15-19, 2014; New Orleans, LA.

http://apps.humana.com/marketing/documents.asp?file=2645201

Predictive meta-modeling to quantify future health risk and identify individuals for clinical programs aimed at improving health outcomes and quality of care

Chui S, Zahedi H, Gopal V. Predictive meta-modeling to quantify future health risk and identify individuals for clinical programs aimed at improving health outcomes and quality of care. Poster presentation at: Society for Medical Decision Making 36th Annual North American Meeting. October 18-22, 2014; Miami, FL.

http://apps.humana.com/marketing/documents.asp?file=2540824

Identifying schizophrenia patients at high-risk for antipsychotic nonadherence using the assessment for quality improvement and risk evaluation tool

Muser E, Slabaugh SL, Louder A, Patel N. Identifying schizophrenia patients at high-risk for antipsychotic nonadherence using the assessment for quality improvement and risk evaluation tool. Poster presentation at: International Society for Pharmacoeconomics and Outcomes Research 18th Annual International Meeting. May 18-22, 2013; New Orleans, LA.

http://apps.humana.com/marketing/documents.asp?file=2574195

Identification of undiagnosed COPD patients in a claims database using a predictive model

Saverno KR, Zhou Y, Moretz C, Renda A, Burslem K, Jain G, Hernandez G, Dhamane A. Identification of undiagnosed COPD patients in a claims database using a predictive model. Poster presentation at: Academy of Managed Care Pharmacy 26th Annual Scientific Meeting and Expo. April 1-4, 2014; Tampa, FL.

http://apps.humana.com/marketing/documents.asp?file=2332005

Data sources and structure for post-licensure rapid immunization safety monitoring (PRISM)

Selvan M, Lee G, Walraven C, et al. Data sources and structure for post-licensure rapid immunization safety monitoring. Poster presentation at: International Society for Pharmacoeconomics and Outcomes Research 19th Annual International Meeting. May 31-June 4, 2014; Montreal, QC, Canada.

http://apps.humana.com/marketing/documents.asp?file=2574611

Optimizing referral to renal care management program through use of a predictive model for transition to dialysis in a Medicare Advantage population

Dong Y, Hines H, Haugh G, Cockrell M, Prewitt T, Gopal V. Optimizing referral to renal care management program through use of a predictive model for transition to dialysis in a Medicare Advantage population. Poster presentation at: Society for Medical Decision Making 37th Annual North American Meeting. October 18-21, 2015; St. Louis, MO.

http://apps.humana.com/marketing/documents.asp?file=2800174

Differences in maintenance vs. acute care between a rural and urban Mississippi Medicare Advantage population with diabetes; a cross-sectional analysis

Majercak K, John P, Hettel C, Eaker E, Renda A, Cusano D, Gopal V. Differences in maintenance vs. acute care between a rural and urban Mississippi Medicare Advantage population with diabetes; a cross-sectional analysis. Podium presentation at: American Public Health Association 143rd Annual meeting and Expo. October 31 - November 4, 2015. Chicago IL.

http://apps.humana.com/marketing/documents.asp?file=2807623http://apps.humana.com/marketing/documents.asp?file=2856906

Evaluating geographic relationship between people and provider by GIS

Luo L, Childers K, Yuan L, Feller S, Northam C, Gopal V. Evaluating geographic relationship between people and provider by GIS. Podium presentation at: Ersi User Conference. July 20-24, 2015. San Diego, CA.

Optimizing medical chart review sample size reduction with a Monte Carlo simulation

Wen Q, Yuan L, Feller S, Gopal V. Optimizing medical chart review sample size reduction with a Monte Carlo simulation. Podium presentation at: American Statistical Association Conference on Statistical Practice. February, 2015; New Orleans, LA.

A novel model for predicting future health risk and cost stratification at a member level

Chiu S, Zahedi H. A novel model for predicting future health risk and cost stratification at a member level.  Podium presentation at: SAS Analytics Conference Series. October, 2014; Las Vegas, NV.

A novel predictive model for identifying members at high risk of falling

Singh H.  A novel predictive model for identifying members at high risk of falling.  Podium presentation at: SAS Analytics Conference Series.  October, 2014; Las Vegas, NV.

Predictive modeling in healthcare: advances in care management

Gopal V, Zahedi H. Predictive modeling in healthcare: advances in care management. Podium presentation at: SAS Analytics Conference. October, 2011; Orlando, Florida.

Validity of diagnostic codes to identify cases of severe acute liver injury in the U.S. Food and Drug Administration's Mini-Sentinel Distributed Database

Lo Re V 3rd, Haynes K, Goldberg D, et al. Validity of diagnostic codes to identify cases of severe acute liver injury in the US Food and Drug Administration's Mini-Sentinel Distributed Database. Pharmacoepidemiol Drug Saf. 2013;22(8):861-72.

http://www.ncbi.nlm.nih.gov/pubmed/23801638

Validation of anaphylaxis in the Food and Drug Administration’s Mini-Sentinel

Walsh KE, Cutrona SL, Foy S, et al. Validation of anaphylaxis in the Food and Drug Administration's Mini-Sentinel. Pharmacoepidemiol Drug Saf. 2013;22(11):1205-13.

Validation of anaphylaxis in the Food and Drug Administration's Mini-Sentinel. - PubMed - NCBI

Understanding predictors of opioid abuse: predictive model development and validation

Dufour R, Mardekian J, Pasquale M, Schaaf D, Andrews G, Patel N. Understanding predictors of opioid abuse: predictive model development and validation. Am J Pharm Benefits. 2014;6(5):208-216.

http://apps.humana.com/marketing/documents.asp?file=2574546

The organizational structure and governing principles of the Food and Drug Administration's Mini-Sentinel pilot program

Forrow S, Campion DM, Herrinton LJ, et al. The organizational structure and governing principles of the Food and Drug Administration's Mini-Sentinel pilot program. Pharmacoepidemiol Drug Saf. 2012;21(Suppl 1):12-7.

The organizational structure and governing principles of the Food and Drug Administration's Mini-Sentinel pilot program.…

Design considerations, architecture, and use of the Mini-Sentinel distributed data system

Curtis LH, Weiner MG, Boudreau DM, et al. Design considerations, architecture, and use of the Mini-Sentinel distributed data system. Pharmacoepidemiol Drug Saf. 2012;21(Suppl1):23-31.

Design considerations, architecture, and use of the Mini-Sentinel distributed data system. - PubMed - NCBI

Can claims-based data be used to recruit black and Hispanic subjects into clinical trials?

Palacio AM, Tamariz LJ, Uribe C, et al. Can claims-based data be used to recruit black and Hispanic subjects into clinical trials? Health Serv Res. 2012;47(2):770-82. doi:10.1111/j.1475-6773.2011.01316.x.

Can claims-based data be used to recruit black and Hispanic subjects into clinical trials? - PubMed - NCBI

A systematic review of validated methods for identifying ventricular arrhythmias using administrative and claims data

Tamariz L, Harkins T, Nair V. A systematic review of validated methods for identifying ventricular arrhythmias using administrative and claims data. Pharmacoepidemiol Drug Saf. 2012;21(1 Suppl):148-53. doi:10.1002/pds.2340.

A systematic review of validated methods for identifying ventricular arrhythmias using administrative and claims data. …

A systematic review of validated methods for identifying venous thromboembolism using administrative and claims data

Tamariz L, Harkins T, Nair V. A systematic review of validated methods for identifying venous thromboembolism using administrative and claims data. Pharmacoepidemiol Drug Saf. 2012;21(1 Suppl):154-62. doi:10.1002/pds.2341.

A systematic review of validated methods for identifying venous thromboembolism using administrative and claims data. -…

A questionnaire to assess the relevance and credibility of observational studies to inform health care decision making: an ISPOR-AMCP-NPC good practice task force report

Berger ML, Martin BC, Husereau D, et al. A questionnaire to assess the relevance and credibility of observational studies to inform health care decision making: an ISPOR-AMCP-NPC good practice task force report. Value Health. 2014;17(2):143-56. doi:10.1016/j.jval.2013.12.011. Erratum in: Value Health. 2014;17(4):489.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4217656/

Using sequence discovery to target outreach for diabetes medication adherence

Lopez A, Long CL, Happe LE, Relish M. Using sequence discovery to target outreach for diabetes medication adherence. Am J Manag Care. 2015;21(11):e601-e608

Using sequence discovery to target outreach for diabetes medication adherence. - PubMed - NCBI

Diabetes Complications Severity Index (DCSI) – update and ICD-10 translation

Glasheen WP,  Renda A, Dong Y. Diabetes Complications Severity Index (DCSI) – update and ICD-10 translation. J Diabetes Complications. 2017;31(6):1007-1013.

http://authors.elsevier.com/sd/article/S105687271631042X

A predictive model for identifying individuals with diabetes at high risk of progression using Diabetes Complication Severity Index (DCSI)

Fan J, Dong Y, Chiguluri V, Glasheen W, Renda A, Prewitt T, Gopal V. A predictive model for identifying individuals with diabetes at high risk of progression using Diabetes Complication Severity Index. Diabetes 2016 Jun; 65(Supplement 1): A602.

Beyond the limits of predictive models: responding to patients’ self-identification of residual readmission risk

Ferries E, Hall B. Beyond the limits of predictive models: responding to patients’ self-identification of residual readmission risk. Poster presentation at: Society for Judgment and Decision Making Annual Meeting. November 19, 2016. Boston, MA.

http://apps.humana.com/marketing/documents.asp?file=3070340

Leveraging predictive modeling to improve the participant identification process for transition to dialysis support programs

Cockrell M, Dong Y, Hines H, Haugh G, Gopal V, Beveridge R, Prewitt T. Leveraging predictive modeling to improve the participant identification process for transition to dialysis support programs. Journal of the American Society of Nephrology. 2015(26):926A.

Validation of febrile seizures identified in the mini-sentinel post-licensure rapid immunization safety monitoring (PRISM) system

Kawai AT, Martin D, McMahill-Walraven CN, et al. Validation of febrile seizures identified in the mini-sentinel post-licensure rapid immunization safety monitoring (PRISM) system. Poster presentation at: Infectious Disease Week. October 8-14, 2014; Philadelphia, PA.

http://apps.humana.com/marketing/documents.asp?file=2574559

Understanding predictors of opioid abuse: predictive model development and validation

Dufour R, Mardekian J, Pasquale MK, et al. Understanding predictors of opioid abuse: predictive model development and validation. Poster presentation at: Academy of Managed Care Pharmacy Nexus 2013. October 15-18, 2013; San Antonio, TX.

http://apps.humana.com/marketing/documents.asp?file=2574533

The Humana database - a data source for pharmacoepidemiologic research

Michels SL, Uribe C. The Humana database - a data source for pharmacoepidemiologic research. Poster presentation at: 28th Annual International Conference for Pharmacoepidemiology and Therapeutic Risk Management. August 23-26, 2012; Barcelona, Spain.

http://apps.humana.com/marketing/documents.asp?file=2574520

Structured advanced care planning facilitated by case managers

Rodkey W, Morrison J, Rackow E. Structured advanced care planning facilitated by case managers. Poster presentation at: Palliative Care in Oncology Symposium. October 24-25, 2014; Boston, MA.

http://apps.humana.com/marketing/documents.asp?file=2645227

Segmentation of a Medicare Advantage population using the Diabetes Complications Severity Index (DCSI)

Chiguluri V, Cusano D, Glasheen W, et al. Segmentation of a Medicare Advantage population using the Diabetes Complications Severity Index (DCSI). Poster presentation at: American Public Health Association 142nd Annual Meeting and Exposition. November 15-19, 2014; New Orleans, LA.

http://apps.humana.com/marketing/documents.asp?file=2645201

Predictive meta-modeling to quantify future health risk and identify individuals for clinical programs aimed at improving health outcomes and quality of care

Chui S, Zahedi H, Gopal V. Predictive meta-modeling to quantify future health risk and identify individuals for clinical programs aimed at improving health outcomes and quality of care. Poster presentation at: Society for Medical Decision Making 36th Annual North American Meeting. October 18-22, 2014; Miami, FL.

http://apps.humana.com/marketing/documents.asp?file=2540824

Identifying schizophrenia patients at high-risk for antipsychotic nonadherence using the assessment for quality improvement and risk evaluation tool

Muser E, Slabaugh SL, Louder A, Patel N. Identifying schizophrenia patients at high-risk for antipsychotic nonadherence using the assessment for quality improvement and risk evaluation tool. Poster presentation at: International Society for Pharmacoeconomics and Outcomes Research 18th Annual International Meeting. May 18-22, 2013; New Orleans, LA.

http://apps.humana.com/marketing/documents.asp?file=2574195

Identification of undiagnosed COPD patients in a claims database using a predictive model

Saverno KR, Zhou Y, Moretz C, Renda A, Burslem K, Jain G, Hernandez G, Dhamane A. Identification of undiagnosed COPD patients in a claims database using a predictive model. Poster presentation at: Academy of Managed Care Pharmacy 26th Annual Scientific Meeting and Expo. April 1-4, 2014; Tampa, FL.

http://apps.humana.com/marketing/documents.asp?file=2332005

Data sources and structure for post-licensure rapid immunization safety monitoring (PRISM)

Selvan M, Lee G, Walraven C, et al. Data sources and structure for post-licensure rapid immunization safety monitoring. Poster presentation at: International Society for Pharmacoeconomics and Outcomes Research 19th Annual International Meeting. May 31-June 4, 2014; Montreal, QC, Canada.

http://apps.humana.com/marketing/documents.asp?file=2574611

Optimizing referral to renal care management program through use of a predictive model for transition to dialysis in a Medicare Advantage population

Dong Y, Hines H, Haugh G, Cockrell M, Prewitt T, Gopal V. Optimizing referral to renal care management program through use of a predictive model for transition to dialysis in a Medicare Advantage population. Poster presentation at: Society for Medical Decision Making 37th Annual North American Meeting. October 18-21, 2015; St. Louis, MO.

http://apps.humana.com/marketing/documents.asp?file=2800174

Differences in maintenance vs. acute care between a rural and urban Mississippi Medicare Advantage population with diabetes; a cross-sectional analysis

Majercak K, John P, Hettel C, Eaker E, Renda A, Cusano D, Gopal V. Differences in maintenance vs. acute care between a rural and urban Mississippi Medicare Advantage population with diabetes; a cross-sectional analysis. Podium presentation at: American Public Health Association 143rd Annual meeting and Expo. October 31 - November 4, 2015. Chicago IL.

http://apps.humana.com/marketing/documents.asp?file=2807623http://apps.humana.com/marketing/documents.asp?file=2856906

Evaluating geographic relationship between people and provider by GIS

Luo L, Childers K, Yuan L, Feller S, Northam C, Gopal V. Evaluating geographic relationship between people and provider by GIS. Podium presentation at: Ersi User Conference. July 20-24, 2015. San Diego, CA.

Optimizing medical chart review sample size reduction with a Monte Carlo simulation

Wen Q, Yuan L, Feller S, Gopal V. Optimizing medical chart review sample size reduction with a Monte Carlo simulation. Podium presentation at: American Statistical Association Conference on Statistical Practice. February, 2015; New Orleans, LA.

A novel model for predicting future health risk and cost stratification at a member level

Chiu S, Zahedi H. A novel model for predicting future health risk and cost stratification at a member level.  Podium presentation at: SAS Analytics Conference Series. October, 2014; Las Vegas, NV.

A novel predictive model for identifying members at high risk of falling

Singh H.  A novel predictive model for identifying members at high risk of falling.  Podium presentation at: SAS Analytics Conference Series.  October, 2014; Las Vegas, NV.

Predictive modeling in healthcare: advances in care management

Gopal V, Zahedi H. Predictive modeling in healthcare: advances in care management. Podium presentation at: SAS Analytics Conference. October, 2011; Orlando, Florida.

Validity of diagnostic codes to identify cases of severe acute liver injury in the U.S. Food and Drug Administration's Mini-Sentinel Distributed Database

Lo Re V 3rd, Haynes K, Goldberg D, et al. Validity of diagnostic codes to identify cases of severe acute liver injury in the US Food and Drug Administration's Mini-Sentinel Distributed Database. Pharmacoepidemiol Drug Saf. 2013;22(8):861-72.

http://www.ncbi.nlm.nih.gov/pubmed/23801638

Validation of anaphylaxis in the Food and Drug Administration’s Mini-Sentinel

Walsh KE, Cutrona SL, Foy S, et al. Validation of anaphylaxis in the Food and Drug Administration's Mini-Sentinel. Pharmacoepidemiol Drug Saf. 2013;22(11):1205-13.

Validation of anaphylaxis in the Food and Drug Administration's Mini-Sentinel. - PubMed - NCBI

Understanding predictors of opioid abuse: predictive model development and validation

Dufour R, Mardekian J, Pasquale M, Schaaf D, Andrews G, Patel N. Understanding predictors of opioid abuse: predictive model development and validation. Am J Pharm Benefits. 2014;6(5):208-216.

http://apps.humana.com/marketing/documents.asp?file=2574546

The organizational structure and governing principles of the Food and Drug Administration's Mini-Sentinel pilot program

Forrow S, Campion DM, Herrinton LJ, et al. The organizational structure and governing principles of the Food and Drug Administration's Mini-Sentinel pilot program. Pharmacoepidemiol Drug Saf. 2012;21(Suppl 1):12-7.

The organizational structure and governing principles of the Food and Drug Administration's Mini-Sentinel pilot program.…

Design considerations, architecture, and use of the Mini-Sentinel distributed data system

Curtis LH, Weiner MG, Boudreau DM, et al. Design considerations, architecture, and use of the Mini-Sentinel distributed data system. Pharmacoepidemiol Drug Saf. 2012;21(Suppl1):23-31.

Design considerations, architecture, and use of the Mini-Sentinel distributed data system. - PubMed - NCBI

Can claims-based data be used to recruit black and Hispanic subjects into clinical trials?

Palacio AM, Tamariz LJ, Uribe C, et al. Can claims-based data be used to recruit black and Hispanic subjects into clinical trials? Health Serv Res. 2012;47(2):770-82. doi:10.1111/j.1475-6773.2011.01316.x.

Can claims-based data be used to recruit black and Hispanic subjects into clinical trials? - PubMed - NCBI

A systematic review of validated methods for identifying ventricular arrhythmias using administrative and claims data

Tamariz L, Harkins T, Nair V. A systematic review of validated methods for identifying ventricular arrhythmias using administrative and claims data. Pharmacoepidemiol Drug Saf. 2012;21(1 Suppl):148-53. doi:10.1002/pds.2340.

A systematic review of validated methods for identifying ventricular arrhythmias using administrative and claims data. …

A systematic review of validated methods for identifying venous thromboembolism using administrative and claims data

Tamariz L, Harkins T, Nair V. A systematic review of validated methods for identifying venous thromboembolism using administrative and claims data. Pharmacoepidemiol Drug Saf. 2012;21(1 Suppl):154-62. doi:10.1002/pds.2341.

A systematic review of validated methods for identifying venous thromboembolism using administrative and claims data. -…

A questionnaire to assess the relevance and credibility of observational studies to inform health care decision making: an ISPOR-AMCP-NPC good practice task force report

Berger ML, Martin BC, Husereau D, et al. A questionnaire to assess the relevance and credibility of observational studies to inform health care decision making: an ISPOR-AMCP-NPC good practice task force report. Value Health. 2014;17(2):143-56. doi:10.1016/j.jval.2013.12.011. Erratum in: Value Health. 2014;17(4):489.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4217656/

Using sequence discovery to target outreach for diabetes medication adherence

Lopez A, Long CL, Happe LE, Relish M. Using sequence discovery to target outreach for diabetes medication adherence. Am J Manag Care. 2015;21(11):e601-e608

Using sequence discovery to target outreach for diabetes medication adherence. - PubMed - NCBI