DETAILED ACTION
Acknowledgements
The present application is being examined under the pre-AIA first to invent provisions.
This office action is in response to the claims filed May 11, 2026.
Claims 1-5, 7-12, 14-18 & 20 are pending and have been examined.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-5, 7-12, 14-18 & 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
In the Instant case, claims 1-5, 7-12 are directed to a process and claims 14-18 & 20 are directed to a product. Therefore, these claims fall within the four statutory categories of invention.
According to the MPEP 2106.04(d), the first prong of the second step of the § 101 analysis (STEP 2A-1) is to determine whether the claim recites an abstract idea, laws of nature or natural phenomena.
Claim 1, for example, recites series of steps for suggesting an order entry based on past care/treatment plan, which is an abstract idea that falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas including managing personal behavior or relationships or interactions between people.
The limitations that set forth the abstract idea are:
generating, […], a rule set for obtaining suggested entries for each of a plurality of components of the CPOE, each rule of the rule set includes a set of patient specific items mapped to a candidate CPOE entry;
obtaining, […], information specific to the patient;
detecting a trigger of a user selection of a component of the plurality of components of the CPOE;
in response to the trigger, determining, […], a suggested entry for the selected component of the CPOE, a support metric for the suggested entry, and a confidence metric for the suggested entry; and
[…]
identifying a rule list from the rule set, the rule list identifying each rule in which the set of patient items of the rule matches at least a portion of the information specific to the patient;
determining a confidence metric for each identified rule based on frequency of co- occurrence of the patient specific items and the candidate CPOE entry of the identified rule in the rule list, and
selecting the candidate CPOE entry of the identified rule with a highest confidence metric as the suggested entry to the selected CPOE component;
The above-noted limitations—obtaining and analyzing past care data of a patient and making and displaying suggestions based on the patient’s past care or treatment data—constitute activities that can be performed mentally or manually by a person using pen and paper, without the need for a computer or other machine.
The second prong of the second step of the § 101 analysis (STEP 2A-2) is to determine whether the claim elements, when viewed individually and as an ordered combination, contain an inventive concept sufficient to integrate the claimed abstract idea into a practical application.
The claim elements in addition to the abstract idea are:
a processor of the adaptive suggestion system
an algorithm to apply the generated rule set to the obtained information specific to the patient with respect to the selected component of the CPOE
displaying the suggested entry for the component of the CPOE on a display of the adaptive suggestion system/user interface.
The additional elements noted above do not integrate the judicial exception into a practical application. More particularly, the claims do not recite additional limitations that: (i) improve the functionality of a computer or other technology or technical field, see MPEP § 2106.05(a); (ii) use a “particular machine” to apply or use the judicial exception, see MPEP § 2106.05(b); (iii) transform an article to a different thing or state, see MPEP§ 2106.05(c); or (iv) provide any other meaningful limitation, see MPEP § 2106.05(e). See also 84 Fed. Reg. at 55.
The processor, algorithm and user display of the adaptive suggestion system, are recited at a high level of generality, and comprises only a microprocessor and memory to simply perform the generic computer functions such as obtaining and analyzing past care data of a patient and making and showing suggestions based on the patient’s past care/treatment data.
Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer/system, or merely uses a computer/system as a tool to perform an abstract idea, does not transform the abstract idea into a practical application - see MPEP 2106.05(f)
The claim does not improve the functioning of any computerized device nor improves another technology or technical process, or provide meaningful limitations beyond generally linking an abstract idea to a particular technological environment or mere instructions to implement an abstract idea on a computer.
The use of the additional elements noted above as tools to implement/automate the abstract idea does not render the claim patent eligible because it does not provide meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment and requires no more than a computer performing functions that correspond to acts required to carry out the abstract idea. See MPEP 2106.05.
Furthermore, the additional claimed elements, noted above, when viewed individually and as an ordered combination does not integrate the abstract idea into a practical application.
STEP-2B of the 101 analysis is to determine whether the claim elements, when viewed individually and as an ordered combination, contain “an inventive concept sufficient to transform the claimed abstract idea into a patent-eligible application.” Alice, 134 S. Ct. at 2357.
The claim does not include additional elements that are sufficient to amount to significantly more than the abstract idea. As discussed above with respect to integration of the abstract idea into a practical application, using the additional element noted above to perform the generic computer functions amount to no more than mere instructions to apply the abstract idea using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible.
The dependent claim further recites computer generic functions that do not integrate the abstract idea into a practical application. These functions include: obtaining datasets of a patient, displaying/showing confidence/support metrics, compiling a list of rules and determining confidence metric for the complied list rules.
Furthermore, the features of the dependent claims when viewed individually and as an ordered combination do not integrate the abstract idea into a practical application. The claims do not improve the functioning of any computerized device nor improves another technology or technical process, or provide meaningful limitations beyond generally linking an abstract idea to a particular technological environment or mere instructions to implement an abstract idea on a computer. The claims also do not include additional elements that are sufficient to amount to significantly more than the abstract idea.
Accordingly, claims 1-5, 7-12, 14-18 & 20 are rejected as ineligible for patenting under 35 U.S.C. 101 based upon the same analysis.
Response to Arguments
Applicants’ arguments with respect to at least claims 1, 14 & 16 have been considered but are not persuasive in connection with the 101 rejections.
35 U.S.C. § 101
Applicant argues (page 10):
Indeed, the claimed invention improves the functioning of a computer to improve the field of medical operations. As described in paragraph [0005] of the Specification, "[t]here is a continued need for methods and systems to streamline and improve the order entry process for CPOEs to reduce EMR fatigue." To address these needs, the additional elements of claim 1 recite an improved user interface for physician orders with user-selectable order components (which is an improvement to computer functionality). See MPEP §2106.05(a)(I) which indicates that an improved computer user interface is considered an improvement to computer functionality. Further, this improved computer user interface addresses the described needs of the field by, in response to selection of such component by a user in the user interface, automatically triggers determination and display of a suggested entry for the selected component.
The examiner, however, respectfully disagrees.
The claim requires user selection and display of suggestion, but it does not specify a particular screen arrangements, navigation behavior or other interface mechanism that changes how the CPOE software functions. The claim does not improve the functioning of any computerized device nor improves another technology or technical process, or provide meaningful limitations beyond generally linking an abstract idea to a particular technological environment or mere instructions to implement an abstract idea on a computer.
Applicant argues (page 10):
Further, amended claim 1 recites a specific method for such improved user-triggered determination of a suggested entry for the selected component by this improved user interface. In particular, claim 1 recites that determination of a suggested entry for the selected component specifically comprises: "identifying a rule list from the rule set, the rule list identifying each rule in which the set of patient items of the rule matches at least a portion of the information specific to the patient;" "determining a confidence metric for each identified rule based on frequency of co-occurrence of the patient specific items and the candidate CPOE entry of the identified rule in the rule list;" and "selecting the candidate CPOE entry of the identified rule with a highest confidence metric as the suggested entry to the selected CPOE component."
The examiner, however, respectfully disagrees.
The amendment specifically shows how the suggested information is chosen. The examiner notes that the selection of data improves the recommendation itself rather than the CPOE technology or interface. The claim does not improve the functioning of any computerized device nor improves another technology or technical process, or provide meaningful limitations beyond generally linking an abstract idea to a particular technological environment or mere instructions to implement an abstract idea on a computer.
Applicant argues (page 11):
Rather than using these known methods to support medical order entry, the claimed invention provides an improved computer user interface for a physician order with user- selectable order components which, in response to selection of such component by a user, automatically triggers determination of a suggested entry for the selected component using a specific, improved method as recited in amended claim 1. Such improved user interface is not a well-understood, routine, or conventional activity in the field.
The examiner, however, respectfully disagrees.
The examiner notes that the matching of patient items to rules, calculation of confidence metrics and selection of the highest ranked candidate are part of the identified abstract idea and do not transform the abstract idea into a practical application. The claims do not specify any additional elements beyond the recited additional elements for data selection, calculations, data analysis and display of a suggested entry.
The claims do not recite additional elements that amount to significantly more than the abstract idea itself, nor do they provide a specific improvement to computer technology as required by Alice Step 2 and MPEP 2106. The use of machine learning, as claimed, is recited at a high level of generality and does not integrate the abstract idea into a practical application. The steps of detecting a trigger or generating a rule set, even if performed by a computer, do not transform the nature of the claim into patent-eligible subject matter.
35 U.S.C. § 103 –
Applicants’ arguments filed May 11, 2026, in connection with the 103 rejections have been fully considered and are persuasive. Accordingly, 103 rejections have been withdrawn.
Prior Art Made of Record
The prior art made of record and not relied upon is considered pertinent to Applicant's disclosure, and is listed in the attached form PTO-892 (Notice of References Cited). Unless expressly noted otherwise by the Examiner, all documents listed on form PTO-892 are cited in their entirety.
Wang et al (ClinicNet: machine learning for personalized clinical order
set recommendations, 2020), discloses:
Scientific advances have led to a wealth of advances in medicine, but
the escalating complexity makes it difficult for clinicians to learn
how to efficiently use all patient information and optimize practice
to the highest quality possible. In this study we develop ClinicNet, a
recommender algorithm that anticipates clinical items (medications,
procedures, consults, etc.) a clinician will order in the hospital based
on prior similar cases. This is similar to online recommender systems
that automatically anticipate your interests and needs. With Clinic-
Net, we can automatically generate lists of clinical order suggestions.
Koutkias et al (Knowledge engineering for adverse drug event prevention: On the design and development of a uniform, contextualized and sustainable
knowledge-based framework, 2012), discloses:
The primary aim of this work was the development of a uniform, contextualized and sustainable knowledge-based framework to support adverse drug event (ADE) prevention via Clinical Decision Support Systems (CDSSs). In this regard, the employed methodology involved first the systematic analysis and formalization of the knowledge sources elaborated in the scope of this work, through which an application-
specific knowledge model has been defined. The entire framework architecture has been then specified and implemented by adopting Computer Interpretable Guidelines (CIGs) as the knowledge engineering formalism for its construction. The framework integrates diverse and dynamic knowledge sources in the form of rule-based ADE signals, all under a uniform Knowledge Base (KB) structure, according to the defined knowledge model. Equally important, it employs the means to contextualize the encapsulated knowledge, in order to provide appropriate support considering the specific local environment (hospital, medical department, language, etc.), as well as the mechanisms for knowledge querying, inference, sharing, and management. In this paper, we present thoroughly the establishment of the proposed knowledge framework by presenting the employed methodology and the results obtained as regards
implementation, performance and validation aspects that highlight its applicability and virtue in medication
safety.
US 20140046696 Al- discloses:
The present invention provides methods and systems or apparatuses,
to analyze multiple molecular and clinical variables from an individual diagnosed with a psychiatric disorder, such as post-traumatic stress disorder (PTSD), in order to
optimize medication selection for therapeutic response. Molecular co-variables include polymorphisms in genes including those involved in central control and mediation of
the hypothalamic-pituitary axis (HPA) stress response, the density of methylation in regulatory regions of said polymorphic genes, polymorphisms in genes that encode cytochrome P450 enzymes responsible for drug metabolism, and drugdrug
and drug-gene interactions. Clinical co-variables include but are not limited to the sex, age and ethnicity of that individual, medication history, family history, diagnostic
codes, Pittsburgh insonmia rating score, and Charlson index score. The system makes a determination based on unstructured and structured data types derived from internal and external knowledge resources to determine psychotropic drug choice that best matches the molecular and clinical variation profile of an individual patient. The decision support system provides a therapeutic recommendation for a clinician based on the patient's variation profile.
US 20060149416 Al- discloses
A system, software, and methods related to enhanced pharmaceutical
order entry and administration by medical personnel, and enhanced pharmaceutical inventory control within a medical institution are provided. An embodiment of
the system includes a pharmaceutical information management server having memory and a medication administration program product including a set of instructions stored in the memory of the pharmaceutical information management server to enhance provision of pharmacy services. The system also includes medical institution physician computers to provide for computerized physician medication order entry, pharmacy computers to provide for review and verification by a pharmacist of electronic medication orders placed through the physician computers, and medical institution
nursing unit computers, to provide for review of and input to electronic medication administration records.
US 20160260035 Al- discloses:
Pharmacy workflow management with alert integration. A pharmacy workflow management application may obtain alert data from an alert generation platform. In turn, the alert information may be provided to a user of the workflow management
application within the application without having to divert from use of the application. The user may further utilize the pharmacy workflow application to access the alert generation platform. In this regard, the user of the pharmacy workflow management application may be in bidirectional communication with the alert generation platform to, for example, exchange resolution information in relation to an alert. The alert data may comprise any pertinent data related to pharmacy activity managed by the pharmacy workflow management application and in particular may include data related to infection control or antimicrobial stewardship.
US 20200185098 Al- discloses:
Techniques for evaluating dynamically modified plans are provided. A selection of a treatment plan template is received, where the treatment plan template specifies a
plurality of treatment stages, where each treatment stage defines a plurality of treatment options. A plurality of modifications to the treatment plan template is generated. It
is determined, for each respective modification of the plurality of modifications, whether the respective modification is permissible, based on one or more predefined institutional
criteria. Upon determining that a first modification of the plurality of modifications is permissible, a first treatment plan is generated based on the first modification to the
treatment plan template. Further, a first predicted efficacy measure is generated for the first treatment plan based on analyzing a knowledge graph. Finally, the first treatment
plan is provided, along with at least an indication of the first predicted efficacy measure.
US 20190392924 Al- discloses:
Embodiments for intelligent recommendation of useful medical actions to a user by a processor. One or more useful medical actions may be cognitively recommended with
evidence in support thereof for impacting a health state of a user according to historical data collected from one or more data sources, one or more user profiles, a domain knowledge, feedback data, or a combination thereof. The one or more useful medical actions may be ranked according to a scoring criteria, the domain knowledge, the historical data, a set of rules, previously recommended medical actions, or
a combination thereof.
US 20200013515 Al- discloses:
The present invention is directed to a drug interaction checking tool for use without medication orders or CPOE which includes an interface sub-system to receive messages from healthcare information technology systems with information
about the patient such as patient allergies, medications the patient is currently taking, patient factors and co-morbidities, where the interface sub-system also receives
messages from a decentralized pharmacy system re withdrawn medications, the clinician, and the patient; a data repository sub-system to store the received data such as patient allergies, medications prescriber, administered or currently in use, patient factors and co-morbidities, medications withdrawn, and the identity of the clinician; access to a medication interactions database; a guidance engine sub-system which performs the medication interaction checks for the patient and generates alerts if a risk of medication errors or adverse reaction is identified; and a notification sub-system which disseminates the alerts to one or more devices and/or systems.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MAMON OBEID whose telephone number is (571)270-1813. The examiner can normally be reached 8 AM- 5 PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Namrata Boveja can be reached at (571) 272-8105. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MAMON OBEID/Supervisory Patent Examiner, Art Unit 3687
