How to Accelerate Clinical Improvement Using Four Domains of Clinical Analytics

Do health systems effectively leverage clinical analytics to drive realoutcomes improvement？Health Catalyst首席临床官、高级副总裁兼临床质量分析总经理Holly Rimmasch在她的问答采访播客开始时提出了这个发人深省的问题。世界杯葡萄牙vs加纳即时走地Although leveraging clinical analytics that result in better care is a complex process, Rimmasch says it is possible, especially with the increased availability ofhealthcare data.

As healthcare organizations use data from increasing sources, organizations are still learning the best way to collect, organize, and distribute the most relevant data to end users. According to Rimmasch, the proliferation of healthcare data and clinical analytics has paved the way for better decision making across the industry.

Four Domains of Clinical Analytics

Drawing from nearly three decades of healthcare experience—from direct patient care to clinical and operational healthcare strategy and various management and executive roles—Rimmasch shared four key aspects of clinical analytics that organizations should carefully consider if they want to achieve sustainable improvement:

#1: Data Acquisition

EHR的出现使医疗保健组织可以广泛地获取以前未见过的临床数据。虽然电子病历有助于了解病人的住院经历，但它并不能提供个人健康状况的全貌。组织还应注重获取其他临床数据，包括影像学、实验室和门诊数据，因为这些数据集还有助于理解其他有健康影响的有价值的数据点，如处方配药和再配药。

Healthcare leaders should consider all data sources along the entire care continuum. EHR data is valuable but often doesn’t include specific information about a patient’s other routine care, such as filling a prescription. However, if a patient fills or refills a prescription, aclaimis submitted with information about the drug, the dose, and the date. This information is significant and useful for the patient’s care team to know, but they can’t access it without claims data in addition to their EHR or clinical data. Therefore, organizations should consider multiple data sources beyond the traditional EHR.

#2: Clinical Analytics Usage

Rimmasch said over her career, she has seen organizations leverage clinical analytics to improve preventive care, end-of-life care, and everything in between. She emphasized two specific ways she has seen organizations use data to advance care:

Target Individual Patients:When patients go to the clinician’s office, the care team uses data to identify at-risk areas they need to address. For example, if the patient has high blood glucose levels, the clinician might put him on a pre-diabetes care plan.

Target Groups: Early in her career, Rimmasch oversaw the care management program at a large healthcare provider and noticed that patients with heart failure would continue to readmit within a few weeks of discharge. When she looked at the heart failure data, she learned that in-person appointments within seven days of discharge, versus the routine phone call, allowed the care team to better assess how patients were faring after discharge and meet their specific needs. Rimmasch applied this analytic insight to the largerpopulation of patients与心力衰竭，以防止不必要的再入院和加速愈合在家里，如果建议的医务人员。

#3: Unrealized Opportunities in Clinical Analytics

Data-driven improvement is a buzzword in healthcare, but there is truth to using data to drive long-lasting improvements, said Rimmasch. She provided a few key areas in which organizations can improve their clinical analytics use to inform better care:

EHR Alerts:To guide better care delivery, organizations can create custom alerts in the EHR-based on their own criteria. To avoid EHR alert fatigue and help the alerts catch provider attention, Rimmasch said that organizational leaders should prioritize the type and number of alerts each day based on the system’s high-priority areas.

Artificial Intelligence (AI) and Machine Learning(ML):Rimmasch said that leaders need to developAIand ML with a deep understanding of the patient and clinician workflow. If leaders create AI and ML in a silo and then implement it in a clinical setting, these advanced tools will become a burden—rather than a benefit—for clinicians.

#4: Patient Engagement

Among the unlimited types of data, the voice of the patient includes some of the most important information. According to Rimmasch, organizations’ clinical analytics should reflect the voice of the patient. Patient engagement tools (e.g.,Twistle™ by Health Catalyst) allow health systems to communicate with patients and engage them throughout the care process. The opportunity to reach out to patients for appointment reminders and care updates keeps the patient aware and involves the patient as part of the care team.

Clinical Analytics Guides Better Care

As healthcare data becomes more widely available, clinical analytics will become increasing vital to delivering better care. Analytic insight from varied data sets helps providers understand what is actually happening compared to what they think is happening and informs clinicians when there is a better way to deliver care.

Rimmasch closed by emphasizing how critical adaptability is throughout the clinical analytics journey. Integrating analytics throughout the entire care process will open leaders’ minds to new opportunities for improvement.

Viewthe full podcast or download the audio only versionhere.

Additional Reading

Would you like to learn more about this topic? Here are some articles we suggest:

• Optimize Your Labor Management with Health Catalyst PowerLabor™
• The Secret Behind Resilient Healthcare Organizations: High Reliability
• Five Practical Steps Towards Healthcare Data Governance
• How Regulatory Compliance Supports Optimal Patient Care and Higher Earnings
• The Right Way to Build Predictive Models for the Most Vulnerable Patient Populations

PowerPoint Slides

你想使用或分享这些概念吗?下载突出重点的演示文稿。

Click Here to Download the Slides