5 “A”s of Evidence-based Medicine & PICOTS: Using “Population, Intervention, Comparison, Outcomes, Timing, Setting” (PICOTS) In Evidence-Based Quality Improvement Work


5 “A”s of Evidence-based Medicine & PICOTS: Using “Population, Intervention, Comparison, Outcomes, Timing, Setting” (PICOTS) In Evidence-Based Quality Improvement Work

Much of what we do when answering key clinical questions can be summarized using the 5 “A” EBM Framework—Ask, Acquire, Appraise, Apply and “A”s Again.[1] Key clinical questions create the focus for the work and, once created, drive the work or project. In other words, the 5 “A”s form a scaffolding for us to use in doing EB quality improvement work of many types.

When healthcare professionals look to the medical literature for answers to various clinical questions or when planning comparative reviews, they frequently utilize checklists which employ the mnemonics, PICO (population, intervention, comparison, outcome)[2], PICOTS (same as PICO with the addition of timing and setting) or less frequently PICOT-SD (which also includes study design.[3]  PICOTS (patient population, intervention, comparison, outcomes, timing and setting) is a checklist that can remind us of important considerations in all of the 5 “A” areas.

PICOTS in Forming Key Clinical Questions and Searching

PICOTS is a useful framework for constructing key questions, but should be applied thoughtfully, because at times all PICOTS elements are not needed to construct a useful clinical question. For example, if I am interested in the evidence regarding prevention of venous thromboembolism in hip replacement surgery, I would want to include the population and study design and perhaps key outcomes, but I would not want to limit the question to any specific interventions in case there are some useful interventions of which I am not aware. So the question might be, “What is the evidence that thromboembolism or deep vein thrombosis (DVT) prophylaxis with various agents reduces mortality and clinically significant morbidity in hip replacement surgery?” In this case, I was somewhat specific about P (the patient population—which frequently is the condition of interest—in this case, patients undergoing  hip replacement surgery), less specific about O (mortality and morbidities) and not specific about I and C.

I could be even more specific about P if I specified patients at average risk for VTE or only patients at increased risk. If I were interested in the evidence about the effect of glycemic control on important outcomes in type II diabetes, I might pose the question as, “What is the effect of tight glycemic control on various outcomes,” and type in the terms “type 2 diabetes” AND “tight glycemic control” which would not limit the search to studies reporting outcomes of which I was unaware.

Learners are frequently taught to use PICO when developing search strategies. (When actually conducting a search, we use “condition” and not “population” because the condition is more likely to activate the MeSH headings in PubMed which produces a search with key synonyms.) As illustrated above, the PICO elements chosen for the search should frequently be limited to P (the patient population or condition) and I so as to capture all outcomes that have been studied. Therefore, it is important to remember that many of your searches are best done with using only one or two elements and using SD limits such as for clinical trials in order to increase the sensitivity of your search.

PICOTS in Assessing Studies for Validity and Synthesizing Evidence

When critically appraising studies for reliability or synthesizing evidence from multiple studies, PICOTS reminds us of the areas where heterogeneity is likely to be found. PICOTS is also useful in comparing the relevance of the evidence to our population of interest (external validity) and in creating decision support for various target groups.

PICOTS in Documenting Work

Transparency can be made easier by using PICOTS when documenting our work. You will notice that many tables found in systematic reviews and meta-analyses include PICOTS elements.


1. Modified by Delfini Group, LLC (www.delfini.org) from Leung GM. Evidence-based practice revisited. Asia Pac J Public Health. 2001;13(2):116-21. Review. PubMed PMID: 12597509.

2. Richardson WS, Wilson MC, Nishikawa J, Hayward RS. The well-built clinical question: a key to evidence-based decisions. ACP J Club. 1995;123:A12–3.

3. Methods Guide for Effectiveness and Comparative Effectiveness Reviews. AHRQ Publication No. 10(12)-EHC063-EF. Rockville, MD: Agency for Healthcare Research and Quality. April 2012. Chapters available at: www.effectivehealthcare.ahrq.gov.


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A Performance Measure for Overuse? The Loosening Of Tight Control In Diabetes


A Performance Measure for Overuse?  The Loosening Of Tight Control In Diabetes

Performance measures for tighter glycemic control appeared following the DCCT trial (Type 1 diabetes) in 1993 and the UKPDS trial (type 2 diabetes) in 1998.[1],[2] About 7 years ago groups recommended that glycohemoglobin concentrations be less than 7%, even though clear evidence of improved net outcomes was lacking.[3]

Now in an editorial in the online version of Archives of Internal Medicine, Pogach and Aron have nicely summarized details of this journey into overuse of hypoglycemic agents resulting in the problem of harms probably outweighing benefits—at least for some diabetics—in an editorial entitled, The Other Side of Quality Improvement in Diabetes for Seniors: A Proposal for an Overtreatment Glycemic Measure.[4]

The authors review the ACCORD, ADVANCE and VADT trials and remind readers that tight glycemic control did not yield cardiovascular benefits in these trials and that severe hypoglycemia occurred in the intensive treatment groups of all three trials. Of concern was the finding that ACCORD was terminated early because of increased mortality in the intensive glycemic treatment group. These trials appear to have increased concern about the risks of severe hypoglycemia in elderly patients and patients with existing cardiovascular disease, and the National Committee for Quality Assurance Healthcare Effectiveness Data and Information Set (HEDIS) modified its glycohemoglobin goal to less than 7% for persons younger than 65 years without cardiovascular disease or end-stage complications and diabetes and established a new, more relaxed goal of less than 8% for persons 65 to 74 years of age.

Kirsh and Aron took this a step further in 2011 and proposed a glycohemoglobin concentration of less than 7.0% as a threshold measure of potential overtreatment of hyperglycemia in  persons older than 65 years who are at high risk for hypoglycemia. They point out that the risk for hypoglycemia could be assessed by utilizing data from the electronic medical record regarding prescriptions for insulin and/or sulfonylurea medications and retrieving information on comorbidities such as chronic kidney disease, cognitive impairment or dementia, neurologic conditions that may interfere with a successful response to a hypoglycemic event.[5]

This commentary is worth reading and thinking about. We agree with them that the time has come to take more actions to prevent the risk of possible overtreatment in diabetes.

[1] The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. The Diabetes Control and Complications Trial Research Group. N Engl J Med. 1993 Sep 30;329(14):977-86. PubMed PMID: 8366922.

[2]  Effect of intensive blood-glucose control with metformin on complications in overweight patients with type 2 diabetes (UKPDS 34). UK Prospective Diabetes Study (UKPDS) Group. Lancet. 1998 Sep 12;352(9131):854-65. Erratum in: Lancet 1998 Nov 7;352(9139):1558. PubMed PMID: 9742977.

 [3]  Pogach L, Aron DC. Sudden acceleration of diabetes quality measures. JAMA. 2011 Feb 16;305(7):709-10. PubMed PMID: 21325188.

[4] Published Online: September 10, 2012. doi:10.1001/archinternmed.2012.4392.

[5]  Kirsh SR, Aron DC. Choosing targets for glycaemia, blood pressure and low-density lipoprotein cholesterol in elderly individuals with diabetes mellitus. Drugs Aging. 2011 Dec 1;28(12):945-60. doi: 10.2165/11594750-000000000-00000. PubMed PMID: 22117094.


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Best Care at Lower Cost: The Path to Continuously Learning Health Care in America


Best Care at Lower Cost: The Path to Continuously Learning Health Care in America

“If home building were like health care, carpenters, electricians, and plumbers each would work with different blueprints, with very little coordination.”

“If airline travel were like health care, each pilot would be free to design his or her own preflight safety check, or not to perform one at all.”

The Institute of Medicine (IOM) has just released this latest “state of our health care” report which is well worth reading. [1]  We have a long ways to go before we have a health system. The report, released September 6, 2012, concludes that our dysfunctional health care system wastes about $760 billion each year. Much of the waste is due to inefficiencies and administrative duplications, but $210 billion of the waste is due to unnecessary services (e.g., overuse, unnecessary choice of higher cost services) and $55 billion is wasted on missed primary, secondary and tertiary prevention opportunities.

Here are just a few of the interesting points and recommendations the 18 authors make:

  • The volume of the biomedical and clinical knowledge base has rapidly expanded, with research publications having risen from more than 200,000 a year in 1970 to more than 750,000 in 2010;
  • We can achieve striking improvements in safety, quality, reliability, and value through the use of systematic evidence-based process improvement methods;
  • We need digital platforms supporting real-time access to knowledge;
  • We need to  engage empowered patients;
  • We need full transparency in all we do;
  • We need improved decision support; improved patient-centered care through tools that deliver reliable, current clinical knowledge to the point of care; and, organizations’ support for, and adoption of, incentives that encourage the use of these tools.

The pre-publication issue of this IOM report is currently available free of charge at this URL.[2]

[1] Smith M, Cassell G, Ferguson B, Jones C, Redberg R; Institute of Medicine of the National Academies. Best care at lower cost: the path to continuously learning health care in America. http://iom.edu/Activities/Quality/LearningHealthCare/2012- SEP-06.aspx.

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