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Institute of Medicine: Delivering High-Quality Cancer Care: Charting a New Course For a System in Crisis; Part V: A Learning Health Care Information Technology System in Cancer Care

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Welcome to part V; part I addressed the current landscape of cancer care, part II addressed patient-centered communication and shared decision-making, part III addressed the work force caring for patients with cancer and part IV addressed the evidence base for high quality care.  Part V focuses on chapter 6 of the IOM’s report.  This chapter focuses on information technology (IT).  The potential for IT to improve the quality of health care and the pace of research was dramatic and mostly unrealized.  Medical records systems were not primarily designed to improve the quality of care, improve coordination of care, or facilitate research to advance care in the future.  Rather, they were designed around billing and coding.  Most cannot even speak to each other.  So, as far as information sharing between providers go, IT has not significantly improved the situation of our grandparent’s generation, when paper charts ruled.

 

IOM dreams of a “learning health care information system.”  The IOM’s vision is rather comprehensive—they envision an IT system that continuously learns.  The system does this by capturing data from patient care and clinical trials prospectively and then implementing this knowledge into clinical practice by feeding it back to providers at the time of decision making.  It then evaluates the outcomes of these changes in care and generates new hypotheses to test and implement in care.

 

Right now, the flow of information in health care is mostly linear—clinical research results inform clinical practice.  In IOM’s vision, the relationship would be more circular—information from clinical practice would also feed back to clinical research to generate new knowledge and new hypothesis for testing.  Right now, the results of clinical trials do not always reach the clinic as fast as they should—the ideal IT system would facilitate rapid translation of new evidence into better care by providing decision support to clinicians.  It would also empower patients in making decisions about their care.

 

Some elements of this system are already in place.  The center for Medicare and Medicaid services has developed “meaningful use” standards for electronic health records along with financial incentives for adoption.  There are three stages.  Stage one has already been implemented—collecting and using data electronically.  Stage two, planned to start in 2014, involves improving and coordinating care.  Stage three, planned for 2016, intends to capitalize on clinical decision support and data collection to improve health outcomes.  The financial incentives for utilization and penalties for lack of adoption have clearly driven many healthcare centers to adopt electronic medical records systems.  The culture of medicine has dramatically shifted from paper-chart centered to computer-centered; any hospital or office that uses paper charts would be seen as old fashioned.  It is less clear to me to what extent this change has or will improve the actual outcomes of the patients served.

 

There are several sources of data for a learning health system that are already in place, doing just what the IOM prescribes.  For example, there are many cancer registries that capture important data on incidence of various cancers, treatments, and their outcomes.  On particularly important registry is the National Cancer Institute’s SEER (Surveillance Epidemiology and End Results Registry).  This database captures cancer incidence and survival from 28% of the US population.  Analyses of this database, with subsequent publications, routinely yield important information.  The report also reviews several other important databases and efforts to develop learning health care systems.

 

IOM says, “A learning health care system facilitates patient engagement.”  If I hadn’t interested, IOM now has my attention.  Most simply, this system gives patients access to their medical records—clinicians’ notes, care plans, and other relevant data.  However, the system should also allow patients to feed information back to providers, such as side effects, relief of cancer symptoms, or trouble filling prescriptions.  With the widespread use of mobile devices such as cellphones and tablets, more rapid communication might be possible—patients could be reminded to take critical pills while doctors could hear earlier about problems.  Some doctors who have not used such a system are fearful that patient access to data could increase patient anxiety and take up valuable face time translating doctor language into patient language; the existing data on such systems, however, reveal a positive experience both for clinician and patient.  Finally, secure electronic messaging could be useful.   I like email as a modality to communicate with patients, but worry about their privacy.  A secure system could facilitate such communication.  This could be particularly useful for patients with speech difficulties (such as head/neck cancer patients).

 

Finally, the ideal IT system should incorporate clinical decision support.  Cancer care is evolving at an extremely rapid pace.  While this is exciting and wonderful, it also creates challenges for already overworked community doctors (remember that upcoming drastic shortfall?)  When patients are waiting unacceptably long after a cancer diagnosis to get an appointment, the community doctor cannot spend a dozen hours per week reading up on new advances in every cancer—actually, if the current pace continues, the advances may make oncology so complex that it is impossible for any human to process it all, unaided by computers.  The ideal system would address this problem by filtering available data and providing the doctor with situation and patient-specific data.  Such provision of information should be integrated with the order entry system.  EPIC, one of the major vendors of electronic health records (as best I can tell, EPIC is dominant nationally, including being implemented at my hospital soon) already offers a medical oncology module that provides information on staging, treatment, chemo and treatment planning.  IOM suggests a final aspect that I find very appealing—when faced with a clinical decision, the doctor should be able to search the IT system for similar situations in the past and rapidly obtain data on outcomes.  If a large database were available for this, it could be very useful for rare cancers and rare situations where clinical trials are often impossible.

 

Perhaps the most controversial part of the IT section is buried in a paragraph about coordinating the cancer work force.  Here, IOM quotes ASCO and I’ll quote IOM, “ASCO envisions nurse practitioners and physician assistants using clinical decision support embedded in a learning health care system to deliver the majority of care in the future.  The oncologist’s role would evolve to focus on managing the care teams, overseeing the development of care plans, collaborating with primary care/geriatric clinicians, and overseeing complex cases.”  Such an approach would surely help address the oncologist shortage problem.  But if care is becoming so complex that our smartest clinicians need a computer to aid cognition, do we want to take the folks with 4 years of premedical science, 4 years of medical school, 3 years of internal medicine residency and 2-4 years of specialty oncology training away from the front lines?  Or do we want them directly caring for our grandmothers with cancer?

 

A quality IT system could improve research, improve the evaluation of quality of care metrics, and assist with fair billing.  For now, there are many challenges to achieving the IOM’s goals.  Currently available health IT is hard to use.  It increases, not decreases the time that it takes to provide quality of care—after a day of seeing patients, I spend hours to accurately chart what happened during the visits. Systems don’t talk to each other—when I want to send a copy of my note to a patient’s geriatrician, for example, it goes by fax or mail, not electronically.  On the other side, it will be filed in paper or scanned into the geriatrician’s electronic system, not properly integrated, as a “universal” electronic system would do.  Electronic health records also have trouble integrating with the databases that, if well formed, could inform future care.  These systems are expensive—very, very expensive.  Patient privacy needs to be protected.  While there are many challenges, electronic health records is clearly the way of the future.  The question at this point is to what extent we can make them do all of the things they had the potential to do.

 

Stay tuned for the final section, which will focus on measuring quality.  This will likely be the briefest of the sections.


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