Monitoring Intensification of Treatment for Hyperglycemia and Hyperlipidemia (Massachusetts)

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Monitoring Intensification of Treatment for Hyperglycemia and Hyperlipidemia - 2010

Summary Highlights

  • Principal Investigator: 
  • Funding Mechanism: 
    RFA: HS07-002: Ambulatory and Safety Quality Program: Enabling Quality Measurement through Health Information Technology (EQM)
  • Grant Number: 
    R18 HS 017030
  • Project Period: 
    September 2007 – December 2010
  • AHRQ Funding Amount: 
    $533,431
  • PDF Version: 
    (PDF, 351.31 KB)


Target Population: Adults, Chronic Care*, Diabetes

Summary: Diabetes quality-of-care measurement is increasingly used to evaluate quality improvement programs and to compare physicians and health plans. Therefore, it is important to know which measures are best associated with clinical outcomes. The most widely used process measures for diabetes quality-of-care, hemoglobin (HbA1c), and low-density lipoprotein (LDL) screening rates have multiple limitations. This project tested the sensitivity and specificity of new informatics tools on improving diabetes quality-of-care measurement.

Poor control of elevated blood pressure and glycosylated HbA1c have been linked to low frequency of treatment intensification. Treatment intensification is defined as an increase in the total daily dose of any anti-hyperglycemic medication and includes either the initiation of a new medication or an increase in the dose of an existing medication. Dr. Turchin and his team developed a physician performance process measure using both structured and unstructured data on the frequency of treatment intensification in managing hyperglycemia and hyperlipidemia. Two informatics tools were developed to determine, based on data from the patient’s electronic health record (EHR), if treatment medication was increased. The first tool extracts structured data from the EHR. The second is a natural language processing tool that assesses whether accurate measures of treatment intensification can be obtained through computational analysis of unstructured text in physician notes.

This project applied the informatics tools to retrospective data generated from an internally-developed EHR, the Longitudinal Medical Record, which was collected in Partners Healthcare System’s proprietary Research Patient Data Registry. The data collected were based on patient visits to primary care practices affiliated with Massachusetts General Hospital and Brigham and Women’s Hospital. By testing the sensitivity and specificity of the measures in a manual review of the electronic patient records, the project determined if the treatment measures obtained through the informatics tools were clinically valid. This research was done by two independent reviewers who did not participate in the tool development. The project used a variety of statistical analyses to demonstrate a relationship between HbA1c and LDL cholesterol levels and two measures of treatment intensification: frequency of treatment intensification, and time to treatment intensification.

Specific Aims:

  • Test the hypothesis that an accurate measure of treatment intensification in the management of hyperglycemia and hyperlipidemia can be obtained through computational analysis of the text of physician notes in the EHR. (Achieved)
  • Test the hypothesis that the measure of treatment intensification developed in the first aim is related to glucose and lipid control. (Achieved)
  • Identify specific patient and visit characteristics that affect the probability of anti-hyperglycemic and anti-hyperlipidemic treatment intensification at a given visit. (Achieved)
  • Test the hypothesis that case mix-adjusted measure of intensification for treating hyperglycemia and hyperlipidemia is more strongly associated with clinical outcomes than currently used process measures of diabetes care. (Achieved)

2010 Activities: Activities focused upon ongoing data analysis and preparation of manuscripts of reported outcomes.

Grantee’s Most Recent Self-Reported Quarterly Status (as of December 2010): The project is complete with all major milestones achieved.

Impact and Findings: The team designed high-fidelity natural language processing tools for identification of treatment intensification in narrative text. Analysis established that narrative and structured data sources provide complementary information about treatment intensification. Data confirm that treatment intensification is strongly associated with faster achievement of both HgA1c and LDL control. High HgA1c and LDL levels were associated with higher probability of treatment intensification while government insurance and female gender were associated with lower rates of intensification. Higher treatment intensification rate and higher HgA1c/LDL testing frequency were associated with higher probability of HgA1c control. The software achieved high accuracy of extraction of medication intensification information from narrative text. The team found that narrative and structured records represented complementary data sources, approximately one third of all intensification records were shared between the two sources, while the rest were unique to either one of them.

In univariate analysis, median time to HgA1c normalization gradually decreased from 1,708 days for patients whose anti-hyperglycemic treatment was intensified less than once every 12 months to 147 days for patients whose anti-hypertensive treatment was intensified more than once every 3 months (p

In multivariable analysis of the factors associated with anti-hyperglycemic treatment intensification for patients with HgA1c = 7.0 percent, the study found that treatment with insulin and higher HgA1c levels were strongly associated with increased probability of intensification while government insurance and female gender were associated with lower probability of intensification. Race and median income by zip code were not significantly associated with anti-hyperglycemic treatment intensification. In multivariable analysis of the factors associated with anti-hyperlipidemic treatment intensification for patients with LDL cholesterol greater than or equal to 100 mg/dL, higher LDL, non-white race, older age, and higher income were strongly associated with increased probability of intensification while having a government insurance, speaking English as the primary language, and female gender were associated with lower probability of intensification.

Strategic Goal: Develop and disseminate health IT evidence and evidence-based tools to improve health care decision making through the use of integrated data and knowledge management.

Business Goal: Knowledge Creation

*AHRQ Priority Population.

Project Details - Ended

Project Categories

Summary:

This project designed and validated a new diabetes quality of care process measure. A method to monitor the new measure was designed utilizing natural language processing (NLP) tools to analyze clinical free-text notes in an electronic medical record (EMR). The project team had previously successfully developed an application which analyzes clinical notes in order to identify treatment intensification of hypertension. This tool will be further developed to identify treatment intensification in the management of hyperglycemia and hyperlipidemia.

The main objectives of this project were to--

  • Test the hypothesis that an accurate measure of treatment intensification in the management of hyperglycemia and hyperlipidemia can be obtained through computational analysis of the text of physician notes in the EMR.
  • Test the hypothesis that the measure of treatment intensification developed in the first objective is correlated with glucose and lipid control.
  • Identify specific patient and visit characteristics that affect the probability of anti-hyperglycemic and anti-hyperlipidemic treatment intensification at a given visit.
  • Test the hypothesis that case mix-adjusted measure of intensification for treating hyperglycemia and hyperlipidemia is more strongly associated with clinical outcomes than currently used process measures of diabetes care.

The project team successfully developed and validated a new diabetes care process measure. They were successful in using NLP tools to identify treatment intensification in narrative text. The project used a retrospective cohort design study to evaluate the treatment of over 20,000 patients with diabetes who were treated in primary care practices affiliated with Brigham and Women's Hospital and Massachusetts General Hospital in Boston, MA.

The project showed that treatment intensification was strongly associated with achieving control of hemoglobin A1c (HbA1c) and low-density lipoprotein (LDL) more quickly than when intensification did not occur or occurred to a lesser extent. Analysis showed that treatment intensification was more likely with high HbA1c and LDL levels. Patients on Medicaid or Medicare were associated with lower rates of intensification, as was female sex. Higher rates of treatment intensification and testing of HbA1c and LDL were both associated with a higher likelihood of control of HbA1c.

Monitoring Intensification of Treatment for Hyperglycemia and Hyperlipidemia in Patients with Diabetes - Final Report

Citation:
Turchin A. Monitoring Intensification of Treatment for Hyperglycemia and Hyperlipidemia in Patients with Diabetes - Final Report. (Prepared by Brigham and Women's Hospital under Grant No. R18 HS017030). Rockville, MD: Agency for Healthcare Research and Quality, 2011. (PDF, 848.85 KB)

The findings and conclusions in this document are those of the author(s), who are responsible for its content, and do not necessarily represent the views of AHRQ. No statement in this report should be construed as an official position of AHRQ or of the U.S. Department of Health and Human Services.
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