Referenced in our first webinar in the series and in more detail in the “Identify” session, this tool walks you through a protocol for mining the existing data in your EHR to find undiagnosed diabetics by examining the relationship between Diagnosis, Labs and Medications. The protocol can be used retrospectively on existing patient data and applied to each individual new patient visit as well to aid in accurate, timely diagnosis.
Similar to the Diabetes protocol, follow this protocol to identify undiagnosed hypertensive patients in your current patient panel. Like the Diabetes protocol, you can use this same protocol with individual patient visits as well. Just replace “Total Patient Population” at the top with a single patient and follow the steps for accurate diagnoses.
In November 2015, funding was received from MDHHS’ Heart Disease and Stroke Prevention Unit to conduct quantitative analysis of Michigan providers. During the second year of analyses, M-CEITA received data from the Medicaid Promoting Interoperability Program (formerly the EHR Incentive Program, AKA Meaningful Use) and Medicare Public Use Files containing information on providers attesting to MU from 2011-2016. The primary goals of the analysis were to analyze MU data reported by Medicaid and Medicare providers related to cardiovascular health and diabetes-specific health outcomes, and identify compelling data patterns from the providers’ MU and CQM reporting. The infographics below include compelling results from this analysis.
These infographics summarize the alarming statistics around Hypertension and Diabetes, and the various ways Health Information Technology (IT) can be used to improve patient outcomes. Each infographic provides support for these solutions by utilizing relevant results from a data analysis project that linked Health IT use to improved patient outcomes. Each document targets a different audience: Patients, Private Practice Providers, and Physician Organizations.
Leveraging Health IT to Engage and Monitor Patients with Hypertension and Diabetes
Leveraging Health IT to Analyze Data and Improve Hypertension and Diabetes Outcomes
Managing Hypertension and Diabetes by Mastering Health IT: Overview
Identifying Hypertension and Diabetes by Mastering Health IT
A wealth of information for any practice looking to incorporate hypertension-related clinical quality improvement initiatives. In our educational webinar series, we stress the importance of evaluating your staff’s BP measurement skills. Page 5 of this guide includes links to videos and assessment tools to measure staff skills and re-train as needed.
Pared with the BP measurement tools and videos referenced in the Million Hearts Hypertension Control Change Package, a step-by-step guide from the Michigan Department of Health & Human Services for proper BP measurement.
An excellent, comprehensive guide for any office looking to incorporate a program of Patient Self-Monitoring of Blood Pressure (SMBP).
A condensed, 2-page “Provider Guide” for implementing a Patient Self-Monitoring of Blood Pressure (SMBP) program at the office level.
(zip file; download then extract)
A fantastic tool for planning/developing/implementing Clinical Decision Support (CDS) interventions. As a bonus, this tool is packed with Hypertension related examples.
A Clinical Decision Support (CDS) starter kit for Diabetes follow-up care with examples that can help you consider how different CDS intervention types can match work processes for a particular clinical condition.
This document represents the official position of the American Association of Clinical Endocrinologists and the American College of Endocrinology for the treatment of Type 2 Diabetes. This comprehensive algorithm should be an integral component in your clinic(s) for improved diabetic outcomes. When the M-CEITA Undiagnosed Diabetes Identification Protocol references a management tool, this is it.
In recent years, Health Information Technology (HIT) has emerged as a promising path toward improving the detection and management of chronic disease. However, for todays’ overstretched clinicians to successfully leverage HIT they need the support, resources, and evidence to show that adopting HIT can positively impact patient outcomes. In 2014, the MDHHS’ Heart Disease and Stroke Prevention Unit and Diabetes Prevention and Control Program partnered with M-CEITA to provide clinicians with educational resources, technical assistance, and evidence to show the impact of HIT adoption on patient outcomes. This paper describes the results from this partnership, discusses the implications for clinicians, and provides a model for other states looking to maximize HIT to improve patient care, chronic disease outcomes, and QI.