Designing an automated clinical decision support system to match clinical practice guidelines for opioid therapy for chronic pain

Abstract Background Opioid prescribing for chronic pain is common and controversial, but recommended clinical practices are followed inconsistently in many clinical settings. Strategies for increasing adherence to clinical practice guideline recommendations are needed to increase effectiveness and reduce negative consequences of opioid prescribing in chronic pain patients. Methods Here we describe the process and outcomes of a project to operationalize the 2003 VA/DOD Clinical Practice Guideline for Opioid Therapy for Chronic Non-Cancer Pain into a computerized decision support system (DSS) to encourage good opioid prescribing practices during primary care visits. We based the DSS on the existing ATHENA-DSS. We used an iterative process of design, testing, and revision of the DSS by a diverse team including guideline authors, medical informatics experts, clinical content experts, and end-users to convert the written clinical practice guideline into a computable algorithm to generate patient-specific recommendations for care based upon existing information in the electronic medical record (EMR), and a set of clinical tools. Results The iterative revision process identified numerous and varied problems with the initially designed system despite diverse expert participation in the design process. The process of operationalizing the guideline identified areas in which the guideline was vague, left decisions to clinical judgment, or required clarification of detail to insure safe clinical implementation. The revisions led to workable solutions to problems, defined the limits of the DSS and its utility in clinical practice, improved integration into clinical workflow, and improved the clarity and accuracy of system recommendations and tools. Conclusions Use of this iterative process led to development of a multifunctional DSS that met the approval of the clinical practice guideline authors, content experts, and clinicians involved in testing. The process and experiences described provide a model for development of other DSSs that translate written guidelines into actionable, real-time clinical recommendations.http://deepblue.lib.umich.edu/bitstream/2027.42/78267/1/1748-5908-5-26.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78267/2/1748-5908-5-26.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/78267/3/1748-5908-5-26-S3.TIFFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78267/4/1748-5908-5-26-S2.TIFFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78267/5/1748-5908-5-26-S1.TIFFPeer Reviewe

An investigation into drug-related problems identifiable by commercial medication review software

BackgroundAccredited pharmacists conduct home medicines reviews (HMRs) to detect and resolve potential drug-related problems (DRPs). A commercial expert system, Medscope Review Mentor (MRM), has been developed to assist pharmacists in the detection and resolution of potential DRPs.AimsThis study compares types of DRPs identified with the commercial system which uses multiple classification ripple down rules (MCRDR) with the findings of pharmacists.Method  HMR data from 570 reviews collected from accredited pharmacists was entered into MRM and the DRPs were identified. A list of themes describing the main concept of each DRP identified by MRM was developed to allow comparison with pharmacists. Theme types, frequencies, similarity and dissimilarity were explored.ResultsThe expert system was capable of detecting a wide range of potential DRPs: 2854 themes; compared to pharmacists: 1680 themes. The system identified the same problems as pharmacists in many patient cases. Ninety of 119 types of themes identifiable by pharmacists were also identifiable by software. MRM could identify the same problems in the same patients as pharmacists for 389 problems, resulting in a low overlap of similarity with an averaged Jaccard Index of 0.09. ConclusionMRM found significantly more potential DRPs than pharmacists. MRM identified a wide scope of DRPs approaching the range of DRPs that were identified by pharmacists. Differences may be associated with system consistency and perhaps human oversight or human selective prioritisation. DRPs identified by the system were still considered relevant even though the system identified a larger number of problems

Development and validation of a clinical and computerised Decision Support System for Management of Hypertension (DSS-HTN) at a Primary Health Care (PHC) setting

Background: Hypertension remains the top global cause of disease burden. Decision support systems (DSS) could provide an adequate and cost-effective m

Clinical decision support system for point of care use--ontology-driven design and software implementation

OBJECTIVES: The objective of this research was to design a clinical decision support system (CDSS) that supports heterogeneous clinical decision problems and runs on multiple computing platforms. Meeting this objective required a novel design to create an extendable and easy to maintain clinical CDSS for point of care support. The proposed solution was evaluated in a proof of concept implementation. METHODS: Based on our earlier research with the design of a mobile CDSS for emergency triage we used ontology-driven design to represent essential components of a CDSS. Models of clinical decision problems were derived from the ontology and they were processed into executable applications during runtime. This allowed scaling applications' functionality to the capabilities of computing platforms. A prototype of the system was implemented using the extended client-server architecture and Web services to distribute the functions of the system and to make it operational in limited connectivity conditions. RESULTS: The proposed design provided a common framework that facilitated development of diversified clinical applications running seamlessly on a variety of computing platforms. It was prototyped for two clinical decision problems and settings (triage of acute pain in the emergency department and postoperative management of radical prostatectomy on the hospital ward) and implemented on two computing platforms--desktop and handheld computers. CONCLUSIONS: The requirement of the CDSS heterogeneity was satisfied with ontology-driven design. Processing of application models described with the help of ontological models allowed having a complex system running on multiple computing platforms with different capabilities. Finally, separation of models and runtime components contributed to improved extensibility and maintainability of the system

IMB 모델 기반 당뇨자기관리 모바일 앱 개발 및 효과 평가

학위논문 (박사)-- 서울대학교 대학원 : 간호학과 간호학 전공, 2017. 2. 박현애.본 연구는 정보-동기-행동기술(Information-Motivation-Behavioral skills) 모델과 근거 기반의 맞춤형 중재를 제공하는 당뇨자기관리 모바일 앱을 개발하고 평가한 후, 당뇨 환자의 당뇨자기관리 행위 및 행위관련요인의 변화로 개발한 앱의 효과를 평가하는 유사실험 연구이다. 당뇨자기관리 모바일 앱 개발 및 평가는 시스템 생명 주기 방법론의 분석, 설계, 구현, 평가 단계에 따라 개발하고 평가하였으며, 당뇨자기관리 모바일 앱의 효과 평가는 총 38명의 당뇨 환자에게 개발한 앱을 4주간 적용하여 사용 전과 사용 후의 당뇨자기관리 행위 및 당뇨자기관리 정보, 개인적 동기, 사회적 동기, 행동기술 등 행위관련요인의 변화를 측정하여 평가하였다. 당뇨자기관리 모바일 앱 개발 및 평가 결과, 분석 단계에서는 당뇨 환자를 대상으로 포커스 그룹 인터뷰를 시행하여 11개의 요구사항 주제(theme)를 추출하였고, 요구사항 주제와 문헌을 근거로 맞춤형 권고 및 교육, 목표 설정, 기록, 공유, 혈당기기 연동 등의 17개 모바일 기능과 당뇨자기관리 행위에 대한 지식을 도출하였다. 설계 단계에서는 당뇨자기관리 모바일 앱의 전체 구성도, 78개의 데이터 모델로 구성된 데이터사전, 10개의 테이블로 구성된 데이터베이스, 알고리즘, 6개의 메인 메뉴로 구성된 메뉴 구성도와 40개의 사용자 화면을 설계하였다. 구현 단계에서는 Android 4.4버젼 이상에서 구현되는 모바일 앱과 서버를 구현하였다. 앱 평가 단계에서 알고리즘 평가 결과 성능도와 능률도 모두 90% 이상으로 나타났고, 휴리스틱 평가에서 나타난 3개의 휴리스틱 문제와 사용성 평가에서 나타난 4개의 사용성 문제는 앱 수정사항에 반영하였다. 최종 당뇨자기관리 모바일 앱의 질은 5점 만점에 3.16점으로 나타났다. 당뇨자기관리 모바일 앱 효과 평가 결과, 당뇨자기관리 사회적 동기 요인과 행위 점수가 유의하게 높아진 것으로 나타났다. 당뇨자기관리 행위 하위 영역 중 특히 자가혈당측정 행위와 문제상황해결 행위가 유의하게 높아진 것으로 나타났으며, 당뇨자기관리 모바일 앱을 활용한 이후 식후 혈당값이 유의하게 감소한 것으로 나타났다. 본 연구에서 개발한 IMB모델과 근거 기반의 맞춤형 중재를 제공하는 당뇨자기관리 모바일 앱은 앞으로 당뇨 환자의 당뇨자기관리에 활용 될 수 있을 것이다.제 1장 서 론 1 제 1 절 연구의 필요성 1 제 2 절 연구의 목적 4 제 3 절 용어의 정의 5 제 2장 문 헌 고 찰 8 제 1절 당뇨자기관리 모바일 앱 기존 연구 8 제 2절 당뇨자기관리를 위한 행위변화 이론 12 제 3 절 정보-동기-행동기술 모델 14 제 3장 이론적 기틀 16 제 4장 연구 방법 19 제 1 절 당뇨자기관리 모바일 앱 개발 및 평가 20 제 2 절 당뇨자기관리 모바일 앱 효과 평가 28 제 5장 연구 결과 36 제 1 절 당뇨자기관리 모바일 앱 개발 및 평가 36 제 2 절 당뇨자기관리 모바일 앱 효과 평가 86 제 6장 논 의 95 제 1 절 당뇨자기관리 모바일 앱 개발 및 평가 95 제 2절 당뇨자기관리 모바일 앱 효과 평가 99 제 7장 결론 및 제언 106 참 고 문 헌 108 부 록 119 Abstract 159Docto