When considering replacing or newly introducing an EMR, vendors' market-share information becomes one basis for judgment. However, because share figures change with the aggregation target and timing, using them directly as your hospital's selection criteria can lead to mistaken judgment.
This article organizes, for hospital decision-makers, how to correctly read share information and how to set selection criteria without over-relying on share. It is explained on the premise of an attitude that treats figures not as definitive but as trends.
How to read share information
Share figures change greatly depending on what the denominator is, at what point in time, and which category is targeted. Whether by number of facilities or by contract value, and whether for hospitals or clinics, the visible ranking differs entirely. Confirming those premises before looking at figures is essential.
In particular, the market structures for hospitals and clinics differ. A vendor strong in clinics is not necessarily equally strong in hospitals, and vice versa. Unless you look at data for a category close to your hospital's size and type, it is not a useful reference.
Treating figures as trends
Share is merely a snapshot at a specific point and is said to fluctuate over time. It is dangerous to declare a certain vendor the best based on a specific figure. Rather, reading trends, such as whether a name stably appears among the top, is more practical.
Also, a high share is one indicator of track record but does not mean the optimum for your hospital. The reason many facilities chose it and whether that reason applies to your hospital need to be considered separately.
Care is also needed with the source of share. Because figures move depending on the surveying body and aggregation method, it is dangerous to speak of rankings without checking which survey is the basis. An attitude of cross-checking multiple sources and seeing whether trends align leads to judgment not swayed by figures.
Perspectives for comparing vendors
It is important to have comparison perspectives against your hospital's requirements, not just share. Lining up candidates along the following axes reveals the substantive differences hidden behind figures.
- Scale fit: whether there is a track record matching your bed scale and department structure
- Department fit: whether it supports the operations and specific forms of your main departments
- Extensibility: whether it is easy to expand integration with department systems and external services over the long term
- Support: whether the post-introduction operational support, incident response, and modification request structure is sufficient
- Future regulatory response: whether the policy and track record for responding to regulatory revisions are shown
Selecting without over-relying on share
Ultimate fit is understood only by actually using it, not from catalogs or share. Confirming through demos and trials whether the main operations of daily work run smoothly for your staff leads to a selection with less regret.
It is efficient to focus the confirmation on high-volume tasks such as outpatient reception, order entry, nursing records, and integration with billing. Having field key persons operate it and gathering candid impressions becomes a basis for judgment that figures cannot measure. Deciding evaluation perspectives in advance lets you compare candidates fairly without drifting into subjective impressions.
The AI-native and cloud-native trend
In recent years, interest is said to be growing in EMRs built on the premise of the cloud and incorporating the use of AI. Considering ease of future regulatory response and functional expansion, whether the design philosophy aligns with the new trend is worth adding as a selection axis. It is important to discern whether it is an extension of the conventional type or designed on new premises.
The EMR Sakigake Prime is an AI-native EMR designed on the premise of using AI atop a cloud foundation, aiming to flexibly keep up with regulatory revisions and feature additions. In comparing with existing vendors, looking at such differences in design philosophy broadens the range of choices.
Common failures and how to avoid them
A common failure is deciding based only on high share. Even if chosen by many, if it does not fit your department structure and scale, operation becomes painful. It is safest to use share as an entry point to narrow candidates, not as the deciding factor.
Another is looking only at features at introduction and slighting post-introduction support and future regulatory response. Because an EMR is a long-used foundation, emphasizing whether the vendor has a structure that can keep up with change curbs the burden in later years. Before contracting, we recommend concretely confirming support response times and the track record of responses at regulatory revisions.
Practical checklist for advancing selection
When advancing selection as practical work, preparing a checklist to avoid missing perspectives makes comparison fair. Evaluating the following items for each candidate on the same criteria clarifies the basis for judgment.
- Whether you confirmed the share category and trend close to your hospital's size and type
- Whether field key persons conducted demos and trials of main tasks
- Whether you confirmed extensibility and external-integration track record with concrete examples
- Whether you confirmed the post-introduction support structure and incident-response track record
- Whether you confirmed the policy for future regulatory response and AI and cloud
Also look at total cost of ownership and migration burden
In selection, it is important to look at total cost of ownership including maintenance, updates, and feature additions, not just initial cost. A configuration that looks cheap but incurs added costs at each expansion or regulatory response can become expensive over the long term. Compare the multi-year cost outlook for each candidate under the same conditions.
The burden of migrating from existing systems cannot be overlooked either. Carrying over past data and retraining staff are said to take considerable time. Evaluating including the migration approach and support structure makes it easier to avoid stalling due to unexpected burden after introduction.
Summary
EMR share information should be read as a trend in light of aggregation premises and is not suited to definitive ranking. Combining perspectives such as scale fit, department fit, extensibility, support, and future regulatory response with hands-on confirmation via demos and trials leads to a selection with less regret. Considering the AI-native and cloud-native trend, judge with the optimum for your hospital as the axis.
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