Center for Healthcare Data Analytics

Expertise

The Center has a rich pool of statisticians and programmers from the Department of Health Care Policy (HCP) with many years of experience working with healthcare claims and survey data. We have six full-time PhD-trained statisticians/biostatisticians. Their research portfolios cover the strategic methodological areas necessary for making scientifically valid conclusions on the basis of large, complex routinely collected databases. Among these, three dimensions are of particular relevance for big data: causal inference, predictive inference, and multi-leveled inference. These areas are critical for discovery: running fast algorithms for data visualization and information retrieval are important, but inferring cause and effect, identifying what treatments work for whom, and determining new areas of investigations require careful, particular expertise.  

Our statistical faculty is at the forefront of many of these larger methodological endeavors. Our research success has benefited over the years from a rich collection of public and private administrative and clinical data and integral relationships between HCP faculty members and government policy makers. Faculty expertise in medicine, economics, and statistics allows us to approach complicated problems related to cost, quality and access in a rigorous, unbiased, and timely fashion. Interactions with researchers in other schools at Harvard or in other universities expands our expertise and skill sets.

Our research staff benefit from a high performance Harvard level 4 certified computational environment which includes over 350 TB of storage attached to two dedicated computational servers with 6 TB of multi-core memory each. This environment is housed at the Markley Data Center in Boston, and stores our CMS Medicare and Medicaid research identifiable files. In addition, researchers have local access to multiple servers, with 18 TB of storage attached to multiple dedicated computational servers, consisting of RAID disk arrays and a Sun 5310 Network Attached Storage system. These systems house diverse array of health care data including medical claims, inpatient charge and payment data (HCBCS), clinical registries, and survey data, as well as supplemental code sets such as the national drug codes (NDC), ICD-9, ICD-10, CPT, and facility type codes.

Programmers

The Center for Healthcare Data Analytics has over 25 programmers, analysts, and data managers working with our statisticians and principal investigators. Many have over 20 years of experience analyzing healthcare data and coding in multiple languages, including SAS, R, Stata, SUUDAN, MLWiN, WinBUGS, MPlus, SPSS, C++. Visual Basic, Python, HTML/CSS, Java, PHP, and SQL. Their expertise covers a broad spectrum of statistical methods from regression analysis and simulations to machine learning and big data analysis. Below is a sample of their expertise.

• Hocine Azeni: 20 years with CMS Medicare, private insurance and state Medicaid data;  5 years with CanCORS, APCD, and VHA data.
• Bob Wolf: 25 years with healthcare data; 20 years with state case mix and claims data; 15 years with registry (STS, ACC-NCDR) data; 7 years with private insurance data; 2 years with survey data.
• Larry Zaborski: 20 years with CAHPS survey data; 5 years with Medicare, VHA, and other healthcare data; 1 year with state Medicaid, claims, and registry data.
• Laurie Meneades: 20 years with "big data" analysis and CMS Medicare data; 5 years with private insurance and survey data sets.
• Marrena Lindberg: 20 years with "big data" analysis; 6 years with survey data; 5 years with other healthcare data.
• Lin Ding: 15 years with survey data (CAHPS); 5 years with HEDIS data; 3 years with registry data and CMS data.
• Katya Zelevinsky: 15 years with registry (STS, ACC-NCDR) and state case mix/APCD data; 5 years with MedStat databases; 4 years with CMS Medicare data and "big data" analytics.
• Jeff Souza: 15 years with CMS Medicare and VHA data; 3 years with APCD, CAHPS, BRFSS and NHANES data.
• Matthew Cioffi: 12 years with registry (STS, ACC-NCDR) and mortality databases (NDI, State); 10 years with BCBS insurance data; 6 years with CMS Medicare and HEDIS files; 6 years with survey data (CAHPS, MIDUS).
• Andrew King: 10 years with Pediatric Health Information Systems, NHANES, APCD and various survey data; has also worked with CMS and BCBS claims data.
• Kayo Walsh: 10 years with survey data (CAHPS); has also worked with MCBS and registry data.
• Maria Petukhova: 10 years with primary data collection; 5 years with NHANES data.
• Barbara Bai: 8 years with "big data" analysis; 4 years with Medicare, Medicaid, private insurance, registry and survey data.
• Pasha Hamed: 6 years with CMS and VHA data.
• Christina Fu: 4 years with CMS and private insurance claims data.