Last month, just before he left home to begin his freshman year at UW-Madison, our son Alex came down with a rash covering the lower portion of both legs. After trying a couple of over-the-counter remedies without any appreciable improvement, I decided to have him checked out at our local BellinHealth clinic.
It took the BellinHealth nurse practitioner Kathy about two seconds to diagnose Alex’s rash as a bad case of poison ivy – most likely picked up at a picnic he went to the previous weekend.
After taking Alex’s temperature and blood pressure, recording his height and weight, and checking to see if he had any drug allergies, Kathy prescribed a steroid for the poison ivy that, in a few days, cleared up the rash and allowed him to head to Madison itch free.
As a person who has spent over 25 years designing and building business computer systems, it never ceases to amaze me how much data is collected during even a brief trip to the doctor. Although Alex has been, thank God, a healthy kid all his life – with only routine exams or the occasional minor athletic injury requiring a doctor visit – the medical file that Kathy updated during last month’s visit must have been four or five inches thick. And this file covered only the last six years of his life!
Like all industries these days, health care is drowning in data. However, unlike most industries, health care has been slow to embrace the processes, technology, and organizational structures needed to turn this vast amount of data into meaningful and timely information to support their internal departments, their patients, and their clinical partners. What is often called Business Intelligence (BI) does not exist in much of the health care world.
Too often, health care organizations are “data-rich, information-poor.”
The adoption of BI by health care organizations has, and continues to be, hindered by several significant challenges, including:
• The difficulty of arriving at an enterprise business intelligence strategy owing to vastly different requirements from multiple (and sometimes competing) business and clinical constituency groups,
• The need to provision real-time data for resource planning, purchasing, and general operational needs,
• The difficulty of providing complex and ever changing health care informatics to support the diverse needs of physicians, patients, administrators, and governmental agencies,
• Extremely large data volumes – especially in organizations that have implemented Electronic Medical Record (EMR) systems – which makes extracting, transforming and loading data time consuming and complex,
• The requirement to integrate structured and unstructured data (some of it subjective in nature) drawn from a wide variety of sources including legacy applications, proprietary databases, paper based systems, and 3rd party medical equipment suppliers,
• The general overall poor quality of much of the data found in health care,
• The need to supply accurate data for benchmarking, utilization, and clinical and financial performance in a dynamic business and clinical environment,
• The challenges of distributing health care information to a wide audience while ensuring the confidentiality of sensitive health information,
• The ever-changing legislative and regulatory demands placed on the health care industry for accurate and timely reporting and business transparency,
• The growing expectations of health care consumers for accurate and timely information to help them control their rising health care costs.
Fortunately, the acceptance of business intelligence by all branches of health care is increasing rapidly. Organizations across the state are stepping up to these BI challenges as never before. It’s estimated that spending on health care business intelligence will grow by about 15 percent in 2008 – with spending increases expected to continue for the foreseeable future.
In order to provide sustainable BI value for the effort, money, and time expended, health care organizations must deploy this capability within the framework of an enterprise-wide business intelligence program with right-sized and scoped tactical BI projects. Experience shows that the best way to develop a health care business intelligence capability is incrementally over time; with individual projects designed to meet high-value business or clinical information objectives.
The time has passed when any health care organization – whether public or private, for profit or not for profit – can succeed without leveraging their considerable clinical and business data assets to enrich their patients’ lives, drive revenue, support compliance and governance, improve quality of care, and reduce health care delivery costs.
