Analytics in Healthcare

An Introduction

Ray Gensinger, Ray Gensinger, Genevieve Melton, Kim Ott, Herb Smaltz, David Garets

• Editorial: HIMSS Publishing
• Año: 2021
• ISBN:
  9781000413700
• Edición: 1
• Categoría: Business
• Categoría: Gestione dell'informazione

The editors of the HIMSS Books' best-seller Health: From Smartphones to Smart Systems have returned to deliver an expansive survey of the initiatives, innovators, and technologies driving the patient-centered mobile healthcare revolution. mHealth Innovation: Best Practices from the Mobile Frontier explores the promise of mHealth as a balance between emerging technologies and process innovations leading to improved outcomes-with the ultimate aim of creating a patient-centered and consumer-driven healthcare ecosystem. Examining the rapidly changing mobile healthcare environment from myriad perspectives, the book includes a comprehensive survey of the current-state ecosystem-app development, interoperability, security, standards, organizational and governmental policy, innovation, next-generation solutions, and mBusiness-and 20 results-driven, world-spanning case studies covering behavior change, patient engagement, patient-provider decision making, mobile gaming, mobile prescription therapy, home monitoring, mobile-to-mobile online delivery, access to care, app certification and quality evaluations, mixed media campaigns, and much more.

CHAPTER 1

A Healthcare Analytics Roadmap

Raymond A. Gensinger, Jr.

If you’ve picked up this book in search of pearls, you are seeking to understand how to build a program of analytics to better your organization. We are all trying to answer some of the following questions:

• Do I really understand the business of healthcare to the fullest extent necessary?
• Am I prepared to answer the really hard questions about the safety, quality, cost, and experience of care that is being delivered?
• Why do the retail, revolving credit, hospitality, and Internet industries know more about assessing patterns and predicting the necessary next actions than does the healthcare industry today?

These represent only the beginning of what seems to be a seemingly infinite number of complicated questions that must be addressed by the healthcare industry RIGHT NOW. The reasons that the time is now for healthcare are detailed at length by the authors in this book, but we’ll introduce them in this chapter.

THE QUALITY AND COST PARADIGM

In the fall of 2012, Consumer Reports examined quality and cost of healthcare based on data from primary care clinics in the Minnesota Community Measurement Program that were collected by HealthPartners.¹ The methodology for the program can be found at Minnesota HealthScores.² According to the article, there were not always strong correlations between the quality of care provided and its cost. When these data were combined, patients could assess the value of the care they could expect to receive at these clinics. Of note, different clinics within the same care system could have relatively wide variations in quality of care provided.

This report reflects the changing healthcare paradigm and highlights that all health-care organizations (HCOs) must either “up their game” to understand the services they are providing or at least begin to learn how to “get into the game” in the first place. HCOs that do not pursue one of these options will have great difficulty in surviving.

Many HCOs are highly effective at descriptive analytics that involve gathering data from their organization and creating representations of the results in tabular or graphic formats. The problem has been that the data were often manually extracted from charts. Transcribers would re-create clinical data entered by nurses, physicians, or other care providers in handwritten notes. Health information management (HIM) staff and coders would translate this information for billing purposes or eventually to help support the justification of admissions through utilization management personnel. Regardless of the end purpose, the process typically included: manual documentation > manual transcription > manual entry into a database or spreadsheet > graphic representation of the results to support the business. Once represented, operational managers and leaders would combine the findings with their experiences in an attempt to project future decisions on construction, staffing, treatment plans, and personnel evaluations.

Such descriptions now seem archaic, given all that we know and can do today. They served our organizations adequately despite the intensity of personnel use required for these manual processes. However, advances in clinical care, clinical computing, and payer sophistication as well as the diverse specialization of providers has made advanced computing and analytics a necessity in today’s healthcare paradigm.

ANALYTICS FOR QUALITY

“Quality” and “safety” are the battle cries for moving the analytics mission forward. Consider the safety perspective of drug recalls, one of the most common yet challenging problems faced by HCOs over the past 30 years. No more than 20 years ago, a drug recall required that a clinician or system review every individual chart to find those patients receiving the particular medication and identify whether a patient had experienced the potential medication/medication or medication/problem interaction. In some cases, the only effective method for identifying these patients was to work backward from the pharmacy, gathering information on patients who had been prescribed a medication and then notifying prescribing physicians of their affected patients. Those lists then would need to be cross-referenced with patient charts to validate that individual patients were still receiving the medication, and the clinician would need to reach out to each patient.

Today’s analytic tools provide a much faster and more thorough understanding of patients and perhaps even correct identification of comorbid conditions or situations that make one population of patients more prone to an adverse reaction or outcome than another population. Answering these questions becomes paramount in a health-care environment advancing at a pace that is no longer comprehensible by individuals, as suggested by the growing healthcare literature (Figure 1-1). At the point in time covered in this graph, the growth rate was still linear. Druss and Marcus³ suggested at the time that clinicians develop active reading skills, watch for prefiltered materials such as reviews and guidelines, and focus on peer-reviewed materials. Today, with the addition of genotypic data to accompany phenotypic data, we may be approaching a logarithmic knowledge growth rate.

Figure 1-1: Growth in number of scientific articles and total pages. Data from Druss and Marcus.³

ASSESSMENTS OF VARIATION

An ongoing challenge between providers and the organizations that employ or host them with medical staff membership is that not all clinicians enter the practice of medicine with the intent of high-quality patient care. Some clinicians expect practice autonomy with very little restriction. Hospitals where they have privileges or the payers with whom they contract might request evidence of their experience in completing certain procedures or care experiences. However, in the past that documentation had no requisite expectation of the quality or outcome of those events. Additionally, once granted those privileges, organizations typically have not required ongoing documentation of the providers’ continued skill or expertise in those privileges.

A typical medical resident applying for new privileges at a hospital likely would have little difficulty documenting the number of times he or she performed central line placements or sigmoidoscopies, managed cardiac arrest, and treated patients with fulminant hepatic or renal failure. However, opportunities to maintain these skills may be limited in practice when the need for such skills becomes infrequent or rare. At what point are skills lost? At what point does the practitioner lose touch with the appropriate standard of care for a particular acute illness?

Internal medicine and family medicine subspecialties offer board certification, with recertification required at 10 and 7 years, respectively. The recertification process can demonstrate a clinician’s ongoing cognitive skills, but physical skills generally are not tested. Insurance carriers have regularly required their providers to maintain a level of expertise demonstrated by an active board certification, but they do not necessarily offer a method of tracking procedural skills.

In 2006, The Joint Commission introduced the ongoing professional practice evaluation (OPPE). This evaluation required organizations to perform continuous monitoring of their medical staff’s performance, quality, and safety as a standard requirement for maintaining privileges (Figure 1-2).

Figure 1-2: Sample OPPE Report. (Reprinted with permission from Ehrenfeld, et al.⁴)

Depending on the technologic infrastructure of an organization, collection and representation of such measures was a labor-intensive chore that was misunderstood (because many Joint Commission standards and expectations are not clearly understood by the typical medical staff member), challenged (because the summarized results were the work of members of a quality or HIM department), or deemed time irrelevant (because the data might represent cases as much as 6 to 12 months old, depending on the sources of the data and elapsed time for organization and representation).

With more sophisticated electronic health record (EHR) infrastructure than was available in 2006, the healthcare industry is much better prepared to deliver not only more timely data but much more comprehensive data that can quickly “link” to the EHR and patient actions. According to the United States Department of Health and Human Services, more than 80% of hospitals have achieved the standards to qualify for health information technology incentives (Figure 1-3).⁵

The use of analytic tools can supply the quality assurance (QA) department and providers with a far better understanding of patients within their report profile, compare providers with their peers, and compare patients with patients of peers. In addition, providers may gain a more detailed understanding of not just the point in time represented by the scorecard but also meaningful...

Índice

• Cover
• Title Page
• Copyright Page
• About the Editor
• About the Author
• Table of Contents
• Foreword
• Preface
• Chapter 1. A Healthcare Analytics Roadmap
• Chapter 2. The Healthcare Analytics Evolution: Moving from Descriptive to Predictive to Prescriptive
• Chapter 3. Application of Analytics to the New Healthcare Paradigms
• Chapter 4. Addressing Current and Upcoming Challenges in Healthcare Analytics
• Chapter 5. Data Mining and Knowledge Discovery from Electronic Health Records
• Chapter 6. Leading and Structuring Analytics within Healthcare Organizations: The Business Intelligence Competency Center
• Chapter 7. Data Governance: Protecting the Gold
• Chapter 8. The Delta Analytics Maturity Model
• Chapter 9. Conclusions
• Appendix. Secondary Use of Data: Learning Modules For Healthcare Providers: A Missing Piece
• Glossary
• Table of Acronyms
• Index