The government’s Meaningful Use measures, and corresponding payments, are intended to incentivize the adoption of EHRs. The HIT Policy Committee recommends that incentives should be paid according to an adoption year rather than a calendar year. This implies that a first year incentive payment would be assessed for eligibility based upon the 2011 measure.
(click here for an extensive Podcast with Shubho Chatterjee)
Let’s review the finalized MU definitions and the associated goals and objectives. The health outcome policy priority is to: “Improve quality, safety, efficiency, and reduce health disparities.” The 2011 objectives are defined as percentages and process checks, such as, (i) use CPOE for all providers or 10% of all orders are through CPOE for Hospitals; (ii) Implement drug-drug, drug-allergy, drug-formulary checks, etc., while the quality measures for these goals are also mostly defined as percentages, such as, 10% of % diabetics with A1c under control, % hypertensive patients with BP under control, % of patients with LDL under control, and others. These measures are to be reported to CMS and are further defined in the NPRM document found on the HealthIT HHS website.
Let us now consider the impact of the need to submit these measures for payment and the process to support the creation and reporting of these measures. CMS defines these measures as a percentage consisting of a numerator and denominator for each measure. For example, to compute the percentage of all orders completed through CPOE during a reporting period, it is necessary to count the numerator as all CPOE issued orders, while the denominator is the count of all orders issued for the reporting period. The numerator can then be divided by the denominator and converted into a percentage.
This very simple measure has enormous procedural complexities associated with the collection, compilation, reporting and display of the data. It is further complicated by the type of data collection or record-keeping system in use – some electronic (structured vs. free-text) some manual, different electronic systems, and by service type and location – Hospital, Long-Term Care, Physician (single or multi-specialty) office, and location/s.
The high-level requirements for reporting these measures are shown in the table below by the record keeping entity.
In the first case — where a single EMR system is used within the service provider system — all CPOE information can be collected, aggregated, and computed for presentation from the system. This may apply to small and medium Physician practices, and small hospitals, and Long-Term Care facilities. However, the question is: does the system have the ability to readily aggregate the counts and determine percentages as required for MU from the existing patient demographics, CPOE, and other treatment functionalities of the system? If not, then programming or system enhancement will be needed to generate the necessary reports.
Other requirements, such as identifying unique patients for eligibility MU measures, necessitate segregating counts to meet this criteria. An added question is the cost/benefit equation to the organization for producing the report for the incentive payments. Additionally, it is highly unlikely that any healthcare service provider will be using a single system. An example is the use of commercial diagnostic testing laboratories and their interfaces for laboratory test orders and results. In this case, if the laboratory provides the statistic, then it will have to be integrated with other measures to provide the MUs required at an aggregate level. The corollary is that, while the MUs can be key in improving the quality of care delivery, it is highly likely significant integration and business intelligence type of developments will be necessary to generate the required MUs.
The second case, and most prevalent, is of an EMR system integrated with other applications, such as other EMRs, other medical applications, or laboratory interfaces. The ability to present an aggregated MU measure is further compounded by the need to gather the data, such as CPOE, from each individual application and calculate, as well as present, the measure. This is further complicated by the age of each system and the underlying data structure, such as free text vs. structured, and the requirement for data mapping or conversions. The conclusion is the same as above.
The third case is of a mix of manual and system or EMR-based order entry. Here the manual data collection is very tedious, error prone, and lacking standardization. Generating the required MU measure/s in this situation will be very labor intensive, depending upon the extent of manual processes for record keeping, also requiring information aggregation with the output of an EMR system.
In summary, regardless of the type of information system — single or mixed — meeting MU reporting requirements will entail significant aggregation and integration of data from multiple systems. How does an organization go about doing that? We specify a simple step-wise process for achieving that objective.
Step 1: Identify and familiarize with all MUs, starting with 2011. Document the measures and data sources using a template shown below with a few examples.
This should clearly identify the data source and the data gathering mechanism. It is obvious that the data gathering and computation efforts will increase significantly where manual processes are involved.
Step 2: Assessment of current information system/s and processes for – (i) availability of the underlying data identified in Step 1; (ii) current systems in use that house the data; (iii) current processes that are used to collect the data, either through a system or manually; (iii) requirements or needs to integrate the data from the data sources.
This step, similar to a gap analysis, will identify existing gaps that need to be filled for generating the measures from the identified data sources. This will, in turn, assist in identifying necessary resources and costs to mitigate the gaps.
Step 3: Cost/Benefit analysis – Completion of Steps 1 and 2 will identify the resource requirements and should be used for a cost/benefit analysis for developing, meeting, and submitting the MUs. The benefit should not only be viewed from the potential incentive payment amount, but from the ability of the organization to create and report actual business and patient-treatment quality impacting measures. The incentive payments are scheduled for six years; the benefits of accurate and timely business and patient treatment quality measures are forever when maintained, and the incentives are a healthy population, lowered healthcare costs, and improved business benefits. Therefore, from a business and patient care quality perspective, the MU concept is indeed good and should be implemented irrelevant of the incentives. The question is more of the timing and a phased approach to meet organizational constraints.
Step 4: Final decision making – In this step, the goal is to balance the cost/benefit analysis with the decision to implement MUs. This decision making should also consider other factors, such as business and technology risks, risk mitigation costs, implementation efforts and schedule, end-user training for MU usage and interpretation, integration of MU measures in the healthcare delivery process, and overall management of the MU program.
Chapter 1 (8:28) Topics Covered — About Miami Jewish; A measured approach to Meaningful Use; The denominator problem; The importance of metrics to process improvement; Coming to healthcare from automotive manufacturing; Toyota Production System
[audio:One-on-One-W-Shubho-Chatterjee-Chapter-1.mp3] Chapter 2 (10:00) Topics Covered — Process improvement methodologies in healthcare; CIO/CEO relations, CIO as change agent; Wireless technologies & the overall IT sophistication of today’s health system; Security and privacy
[audio:One-on-One-W-Shubho-Chatterjee-Chapter-2.mp3] Chapter 3 (10:16) Topics Covered — Security, stability & storage; CIO & activity-based costing; When and how to use consultants; Meditech and Miami Jewish’s IT shop; HIT workforce shortage; Feelings on HITECH & the Meaningful Use bar
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