Question

In terms of alternative payer models (APMs) ,what is the business and clinical case for use of enterprise data, and what are the challenges with bringing data systems online? How does an Enterprise strategy for the use of data helps to inform valid and reliable data for eCQMs?

Answer 1

An efficient, integrated health services delivery enterprise requires the ability to coordinate service delivery across the provider network and avoid duplication of services. It must be able to associate relevant clinical information with patients regardless of which facility delivered the services. There are significant challenges in collecting, organizing, and extracting value from data collected in the course of providing healthcare.

All data comes from somewhere, but unfortunately for many healthcare providers, it doesn’t always come from somewhere with impeccable data governance habits. Capturing data that is clean, complete, accurate, and formatted correctly for use in multiple systems is an ongoing battle for organizations, many of which aren’t on the winning side of the conflict. For example in one recent study at an ophthalmology clinic, EHR data matched patient-reported data in just 23.5 percent of records. When patients reported having three or more eye health symptoms, their EHR data did not agree at all. Poor EHR usability, convoluted workflows, and an incomplete understanding of why big data is important to capture well can all contribute to quality issues that will plague data throughout its lifecycle.The main challenges are

1. Program Design Challenges: The eCQM specifications were complex, difficult to access, contained inaccuracies and were not maintained over time, creating confusion and additional work.

2. Technology Challenges: The eCQM tools from vendors did not work as expected and could not efficiently generate accurate measure results.

3. Clinical Challenges: The eCQM implementation process negatively affected clinicians, adding to their workload with no perceived benefit to patient care as it duplicated information already entered in narrative text. The process also failed to generate usable data to support quality improvement efforts.

4. Strategic Challenges: Hospitals expended excessive effort on the eCQMs that negatively affected other strategic priorities.

Enterprise strategy for the use of data helps to inform valid and reliable data for eCQMs for  example venous thromboembolism (VTE) includes deep vein thrombosis (DVT) and pulmonary embolism (PE); both of which are frequent complications associated with hospitalization and affect the morbidity, mortality, length of stay and costs of millions of patients each year throughout the world. Medical as well as surgical patients are at risk during their hospital stay. There are a number of known and suspected combinations of risk factors for VTE and manual surveillance for the high-risk patients was too time-consuming to be done reliably every day. We selected a previously published high-risk score that included individual risk factors that were found in our EDW54. A VTE data mart and new SQL queries were developed that collected and stored the presence of each risk factor identified for any patient found in the encounter table during the nightly search. Patients with a score of 4 points or higher are identified as high risk for VTE. Cancer, previous VTE and hypercoagulability is scored as 3 points, surgery duration greater than one hour as 2 points and age > 70 years, bed rest, body mass index (BMI) > 29 kg/m2 and use of hormone-replacement therapy or oral contraceptives as 1 point each. Thus, patients could be identified as high-risk at admission or later as they accumulate more risk factors such as surgery duration or bed rest.

So future policy requirements for eCQMs must consider the effort required and the capability of reporting specific eCQMs from certified EHRs. Specifically, the challenges identified in this study must be used to inform future plans and efforts to ensure eCQMs provide meaningful performance results that lead to improved patient outcomes. Many hospitals, including the four facilities studied for this report, have shown a commitment to using their EHRs and eCQMs as a method to automate the quality measurement process. Even the most advanced hospitals have been unable to use their EHRs to efficiently implement the eCQMs and achieve accurate results. Hospitals have expended large amounts of financial and personnel resources in their efforts to make the process work