Data as a Service

With a wealth of historical and aggregated data, d2i is uniquely positioned to perform actionable analysis.

d2i has been acquiring and curating data for performance analytics to improve quality, optimize Emergency Department (ED) operations, and increase patient satisfaction for more than 10 years. Through these efforts, we have developed a longitudinal data set of more than 25 million ED and inpatient visit records, with more than 7 million new visits and admissions being added annually.

Data as a Service (DaaS) provided by d2i represents the richest and most reliable data sets from emergency medicine operations available today. Some of the largest independent physician groups rely on d2i for data to enable a broad range of operations, as well as clinical performance and process improvement initiatives.

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Our process ensures trusted, relevant, and actionable data.

d2i collects data from diverse sources, integrating it into repositories that are many times more valuable than their independent parts. This data is also aggregated across hundreds of sites and millions of visits to establish new knowledge and benchmarks for our clients.

Data Acquisition. d2i has developed data extract scripts for most of the electronic health records (EHRs) and emergency department information systems (EDISs) on the market. These data extract scripts have been implemented by hospital IT hundreds of times.

Data Integration. A repeatable data mapping process is tailored for each ED site’s unique EHR implementation and operation.

Data Cleansing. Rigorous automated data cleansing routines leverage algorithms populated with client-based data.

Data Normalization. Automated processes are used to harmonize billing and EHR data with other data sources.

Data Enrichment. New data is transformed and validated to create and allow for more dynamic ways to relate, organize, and filter data for more advanced analysis.

Data Curation. Historical and aggregated data are maintained for benchmarking, patterns, and trends.

Strategic Initiatives
  • Benchmarking: Meaningfully comparing performance metrics against internal goals, across multiple sites, and against local, regional, or national standards.
  • Clinical Intelligence: Understanding the impact that operational metrics and clinical practice patterns (for example, prescribing patterns and CT utilization) have on practice variation, patient outcomes, and readmissions.
  • New Product Development: Understanding customer attitudes toward medical problems and current therapies through data-driven studies.
  • Marketing/Product Management: Building a business case for investing in new products and marketing programs through market segmentation.
  • Competitive Intelligence: Understanding usage patterns and outcomes for competitive products and therapies.
  • Strategic Planning: Assessing a broad range of market patterns and trends in order to evaluate and compare investments and potential acquisition targets.
DaaS Database Groupings

DaaS offers hundreds of data fields across the following database groupings, including:

EHR Data

  • Patient demographics
  • Patient histories, including medications, allergies, and immunizations; social, family, and surgical histories; and problems and complaints.
  • All clinical events, including pharmacy, radiology, and lab orders and results.
  • LOINC, RxNORM
  • All patient events, including patient movement, clinician touch points, and time stamps.
  • Unstructured data from clinician notes

Time Accounting Data

  • Shifts
  • Clinician scheduled hours
  • Actual hours worked

Billing Data

  • All billing transactions
  • AR data
  • Payer data
  • Coding data
  • E&M
  • ICD10
  • CPT

Patient Satisfaction

  • Date of service
  • Answers to survey questions
Areas Targeted for Performance Improvement
  • Clinical variation and protocol compliance
  • Operational effectiveness and efficiency
  • Billing completeness and accuracy
  • Professional staff productivity
  • Malpractice and patient safety risk
  • Scheduling optimization
Partial List of Key Metrics
Operations

  • Average visits per day
  • Admit to IP and admit to observation status, percentage of total visits
  • LWBS and AMA (left without being seen and against medical advice)
  • Average minutes, from door to first provider
  • Median turnaround time (TAT), discharged and admitted patients
  • Average wait times
  • Average length of stay (ALOS)

Financial

  • Cost per visit hour
  • Average charge per billed visit
  • Average RVUs per doc/APP hour
  • Patients billed E&M 99821–99283 where CT, MRI, IV, or ultrasound is utilized

Clinical

  • CTs ordered per 100 patients
  • Patient arrival time to first antibiotic for relevant diagnostic subgroups
  • Patient arrival time to EKG ordered for relevant diagnostic subgroups
  • Readmissions

Patient Satisfaction

  • NRC Picker scores
  • Press Gainey scores
  • Number of surveys
  • Average patient satisfaction for MD measures only
Sampling of Analytic Storyboards Available out of the Box
  • Impact of census on ED crowding, ALOS, and LWBS
  • Impact of point-of-care testing on patient flow and quality
  • Impact of APP staffing on utilization of various tests, and ALOS and cost/visit hour
  • Impact of Alternative to Opioids (ALTO) Initiative on opioid prescribing patterns
  • Impact of behavioral health patient census on patient flow and ED crowding
  • Impact of fast-track program on patient flow
  • Impact of dynamic staff scheduling on patient flow, cost, and ED crowding
  • Impact of IP bed availability on ED boarding
  • Impact of LWBS and AMA on ED and inpatient revenues