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2 The Culture of Health CareHealth Care Processes and Decision Making Welcome to The Culture of Health Care: Health Care Processes and Decision Making. This is Lecture d. The component, The Culture of Health Care, addresses job expectations in healthcare settings. It discusses how care is organized within a practice setting, privacy laws, and professional and ethical issues encountered in the workplace. Lecture d This material (Comp 2 Unit 4) was developed by Oregon Health & Science University, funded by the Department of Health and Human Services, Office of the National Coordinator for Health Information Technology under Award Number IU24OC This material was updated in 2016 by Bellevue College under Award Number 90WT0002. This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. To view a copy of this license, visit

3 Health Care Processes and Decision Making Learning ObjectivesDescribe the elements of the “classic paradigm” of the clinical process (Lecture a). List the types of information used by clinicians when they care for patients (Lecture a). Describe the steps required to manage information during the patient-clinician interaction (Lectures a, b, c). List the different information structures or formats used to organize clinical information (Lecture b). Describe different paradigms and elements of clinical decision making (Lectures a, b). Explain the differences among observations, findings, syndromes, and diseases (Lectures a, b, c). Describe techniques or approaches used by clinicians to reach a diagnosis (Lectures a, b, c, d, e). List the major types of factors that clinicians consider when devising a management plan for a patient’s condition, in addition to the diagnosis and recommended treatment (Lecture e). Describe the role of EHRs and technology in the clinical decision-making process. (Lectures a, b, c, d, e). The objectives for Health Care Processes and Decision Making are: Describe the elements of the “classic paradigm” of the clinical process. List the types of information used by clinicians when they care for patients. Describe the steps required to manage information during the patient-clinician interaction. List the different information structures or formats used to organize clinical information. Describe different paradigms and elements of clinical decision making. Explain the differences among observations, findings, syndromes, and diseases. Describe techniques or approaches used by clinicians to reach a diagnosis. List the major factors that clinicians consider when devising a management plan for a patient’s condition, in addition to the diagnosis and recommended treatment. Describe the role of EHRs and technology in the clinical decision-making process.

4 Choosing Therapy: The MythThe clinical process: Patient presents with problem  n x Diagnosis  Treatment  Problem resolution Clinician may incorporate scientific evidence to choose appropriate treatment This view is overly simplistic This lecture will focus on the issue of deciding how to treat or manage the patient’s problem once it’s diagnosed. It’s easy to think of the clinical process as a fairly straightforward, linear, discrete series of steps. According to this linear view, the clinician starts with a patient care problem, proceeds to determine a specific diagnosis, then incorporates scientific evidence and often local organizational imperatives to choose an appropriate treatment, resulting in resolution of the problem. The clinical process may occur in this fashion on occasion, but in most cases, the linear view is overly simplistic.

5 Choosing Therapy: RealityA more realistic view is depicted in this slide. Once again, the process begins with the patient care problem. The clinician generally tries to reach a specific diagnosis, but often the diagnosis can’t be determined, or the clinician needs to begin management of the process before diagnostic testing is complete. A diagnosis isn’t always available or necessary to move on to problem management. With a working diagnosis in hand, the clinician can incorporate scientific evidence and organizational imperatives to make a decision about management; however, other considerations often exist that must be taken into account. First among these are coexisting conditions, current or past illnesses, and medications that have an impact on treatment decisions for a new problem. For example, a patient with kidney disease may not be able to metabolize certain medications. In a patient with diabetes, it may be desirable to treat high blood pressure in a different way than in other patients. Clinicians must also take into account the patient’s preferences when devising a management plan. The growing movement toward patient-centered care and the expanded use of tools such as interactive decision aids, patient portals, personal health records, and secure electronic messaging have increased the process of “shared decision making.” In this process patients and clinicians [quote] “work together to make decisions and select tests, treatments and care plans based on clinical evidence that balances risks and expected outcomes with patient preferences and values.” [end quote] Social factors, such as the patient’s job, significant others, family members, and current housing situation, may also have a bearing on treatment choices. Another set of considerations are local practices. These are relevant not just in rural areas, where resources or expertise may be constrained, but also in tertiary medical centers where local experiences or preferences for particular procedures or treatments may differ from the experiences or preferences at other institutions. Ideally, we hope a clinician’s choices are driven solely by scientific evidence and the other factors discussed earlier; however, scientific evidence alone may not fully address a clinician’s questions, and the experiences and preferences of local specialists may be significant factors. Furthermore, the experience of the clinician has some bearing on the best treatment choice for the patient. In general, a clinician performs better doing a procedure that he or she is familiar with than doing a new one. The same applies to prescribing familiar versus unfamiliar drugs. This issue is addressed well in Gawande’s [ga-wahn-deez] book Complications. This doesn’t preclude a clinician referring a patient to another clinician or a specialist who has more experience in a particular medical area or routinely performs a specific procedure. Last, but by no means least, are economic constraints. The most highly recommended, scientifically supported medication or treatment simply may not be available to a patient depending on his or her insurance plan or economic situation. All of these factors must be taken into account when devising a plan to manage the patient’s problem. 4.8 Figure: The complex and dynamic processes that are in play when a patient care problem has to be translated into problem management by the clinician (Mohan, 2010)

6 Individualizing ManagementCoexisting conditions Patient preferences Social factors Economic limitations Scientific evidence Local practices Personal (clinician) experience Organizational imperatives HTN in DM – choose ACEI PSA test – patient preference Hmong beliefs about death New murmur, no insurance PPI over H2 blocker for GERD Specialist availability, beliefs Choice of surgical procedure Formulary of insurance plan Listed here are specific examples of the kinds of considerations that the clinician must address to individualize management options for the patient. The first example is coexisting conditions. A patient with high blood pressure who also has diabetes should be treated first with a type of drug called an ACE [ayse] inhibitor because these medications have special and distinct benefits when they are used in diabetic patients. Second, patient preferences may well drive whether or not a prostate screening test called a PSA [P-S-A] should be ordered. A third example is a person dying of lung cancer who is an Hmong [hmawng] immigrant from Laos who would prefer not to die at home, contrary to the usual assumptions about in-home hospice provision in palliative [pal-ee-uh-tiv] care. Economic limitations come into play, for example, when a new heart murmur is discovered but the patient has no insurance to pay for diagnostic testing; here, a wait-and-watch approach might be taken. For a patient with peptic ulcer disease and heartburn, scientific evidence would drive the decision to choose a class of drug called a proton-pump inhibitor instead of another class called a histamine blocker; however, the better agent is more expensive, and price may be a concern. Local practices may come into play when determining referrals for procedures in specialty care. Well-trained and well-regarded specialists may have different preferences when treating certain conditions. A clinician’s own experience is relevant when choosing medications or treatments because, in general, that clinician will perform better and more safely when using a familiar procedure or drug than when using an unfamiliar one, even if the new one is said to be better. Finally, organizational imperatives may drive choices beyond what the clinician and the patient think is best, such as when the formulary of a health plan or hospital restricts the choices of certain drugs within a particular category.

7 Decision Analysis List options availableList possible outcomes of each option Find probability of each possible outcome Ask patient for utility of each outcome (e.g., time trade off) Calculate expected utility of decision Toss ups Heuristics and biases As mentioned earlier, a formal approach can be taken when making decisions about interventions using a technique called decision analysis. In most cases, this technique is too complex for use at the bedside or in individual decisions. It’s more often used to determine health care policy or guidelines. In certain circumstances, however, if the problem is well formulated and the data is available, decision analysis can be applied to individual patients. This slide illustrates a conventional decision-analysis tree where three options are available for the treatment of a patient diagnosed as having anginal [an-jahyn-l] chest pain following a coronary artery bypass graft; the three choices are medical treatment, angioplasty [an-jee-uh-plas-tee], or another bypass. For each of these choices, the patient may have similar outcomes of improvement, deterioration, or death. Each of these outcomes has a different probability depending on the treatment that is rendered and a different utility depending on the patient’s preferences. If we can determine these utilities (or dis-utilities) and probabilities with sufficient precision, we can actually calculate the expected value of each choice to determine the preferred choice. However, in some circumstances, known as toss ups, even decision analysis can’t lead to a final determination because it’s too close to call. These scenarios are called preference-sensitive decisions, meaning that they depend more on the preferences of the patient than on the treatment results. Decision analysis has also been used to help clinicians understand their biases in cases where their decisions don’t match what this formal decision-analytic procedure would predict. Another mathematical approach that is typically used to set policy and devise guidelines is cost-effectiveness analysis. For example, if the question is whether men at risk for gastric cancer should undergo early endoscopic [en-duh-skop-ik] evaluation, a model is created that reflects the options available and the possible outcomes for individuals who undergo these options. The calculation is performed based on the assumption that these choices are made for an entire population, and this calculation determines the cost effectiveness, or incremental cost effectiveness, of performing the procedure for differing age groups. Although this information is used mainly for setting policy, it can be used in some cases to help with individual treatment decisions. 4.9 Chart: Decision analysis chart (Mills, 1991)

8 SOAP Process Model 4.10 Figure: By CAST, CC-BYThis slide illustrates the SOAP [soap] note format introduced by Lawrence Weed in his 1968 landmark article, “Medical Records That Guide and Teach.” This management tool was widely adopted in health care after its publication. According to this format, notes in the clinical record are recorded using the same structure for each patient problem. SOAP stands for subjective, objective, assessment, and plan. Subjective pertains to information obtained from the patient, and objective represents observations made by the clinician or obtained from the laboratory. Assessment refers to the clinician’s determination of the problem and its severity, and plan is a management plan for this particular patient at this particular time. Note that the structure of Weed’s SOAP note matches that of scientific argument, beginning with a statement of the problem, followed by presentation of the data, interpretation of the data, and conclusions about what should be done. Weed intended that clinicians would enforce this order to help them think clearly, considering the data before reaching a conclusion. The logic is embedded in the structure, and entering this information in a different order might result in different conclusions. Another aim of this system is to produce continuity over time. Weed suggested that each problem be given a specific number and that these numbers be used in each case that addresses this problem so that a particular condition can be followed over time. As predicted by Weed nearly 50 years ago, electronic medical records make this continuity much easier to achieve. Clinical information systems, electronic health records, and clinical decision support systems are just some of the electronic tools and technology used to support the patient’s management plan—especially when the patient requires care from multiple providers in various settings. Electronically sharing the patient’s management plan with all participating providers facilitates effective transitions of care across the patient care continuum. Ideally, all providers on the care team should have access to and contribute to the patient’s record, which provides a holistic view of the patient. Health information exchange also supports the industry’s ability to move toward value-based care insurance models as we move away from traditional insurance models. 4.10 Figure: By CAST, CC-BY

9 “Medical Records That Guide and Teach” (Weed, 1968)Plan Diagnostic Therapeutic Patient education Three-part plan reminds clinician of uncertainty, patient inclusion Continuity over time You see in this slide that a plan is divided into three parts: diagnostic, therapeutic, and patient education. Following this three-part plan reminds clinicians to think about each part separately and to include a patient-education plan for every problem.

10 Management Plan SOAP Format Problem 1: Polydipsia, polyuriaDx: Blood sugar, hemoglobin A1c, urinalysis Tx: Diabetic diet, exercise prescription Pt. education: Meet with diabetic educator, referral to local diabetes group Problem 2: High blood pressure Dx: EKG, urinalysis, serum electrolytes Tx: Low-salt diet, exercise prescription, diuretic Pt. education: Hypertension handout, list of useful websites Here’s a sample of such a plan. The words diagnosis and treatment are replaced by the term management plan as a reminder that an exact diagnosis is often not available when the plan is made—and may never be. In many cases, the outcome is not a treatment plan but a management plan—one that includes diagnostic testing or monitoring; other elements of management besides treatment, especially for conditions that are not treatable; and patient education and engagement.

11 Management Plan ContinuedGI Initial Plan Secondary Tertiary GERD Trial of medication f/u appt for decision EGD PUD/bleeding Labs H pylori therapy ($$$) Gastritis Education re lifestyle changes Non-ulcer dyspepsia (Diagnosis of exclusion) Gallbladder, pancreas CT or US Zebras: cancer, etc. EGD or CT if unimproved Another consideration, especially in primary or ambulatory care settings and for chronic conditions, is staging the management plan. In some cases, diagnostic tests or treatment interventions are needed only if the initial testing or initial treatment does not remedy the problem. In the hospital, with its foreshortened time horizon, staging the plan is much harder to accomplish, but in the outpatient setting it’s commonly done. This simple table represents an evolving management plan. Across the top are columns for the initial plan, the secondary plan, and the tertiary plan. In the first row under GI [G-I], or gastrointestinal, conditions, the patient appears to have heartburn or gastroesophageal [gas-troh-ih-soff-uh-jeeuhl] reflux disease. The initial plan is a trial of therapy with a proton-pump inhibitor, which works in about 80 percent of cases. If this drug is not effective, then the plan is for the patient to come back and a decision needs to be made about further workup, possibly including a diagnostic test called esophagogastric [eh-soff-uh-goh-gas-trik] duodenoscopy [doo-awd-ehn-ah-skuh-pee], or EGD, which is usually definitive but always expensive. In the second row, peptic ulcer disease with bleeding is being considered. The initial plan is to obtain blood tests to see whether anemia has developed or there’s blood in the stool. If both of these prove to be normal, then no further steps will be taken. If either test is abnormal, then the secondary plan involves an esophagogastric duodenoscopy. If that test shows the disease is caused by Helicobacter [hell-ih-coh-bak-ter] pylori [pie-lawr-ee], a germ that causes ulcers, then treatment for that condition will be given. This treatment, however, may be expensive and may be restricted by some health plans. The logical procedure, therefore, is to follow this evolving plan that proceeds through stages depending on the results of the preceding stage. Again, although such a staged management plan may be the ideal, it’s difficult to execute in the hospital because of the very short time horizon and the need to discharge patients as quickly as possible. It’s similarly difficult to execute in the ambulatory care setting because of substantial constraints on clinician time and patient access. Cardiac Initial Plan Secondary Tertiary CAD Education re lifestyle changes Exercise stress testing Aspirin? 4.11 Table: Evolving Management Plan (Mohan, 2010)

12 Health Care Processes and Decision Making Summary – Lecture dThis lecture examined Models that clinicians use to choose therapy and formulate a management plan The process of individualizing patient management Techniques that assist in formulating a management plan: Decision analysis SOAP notes This concludes Lecture d of Health Care Processes and Decision Making. In summary, this lecture examined models that clinicians use to choose therapy and formulate a management plan. The process of individualizing patient management was discussed, along with techniques such as decision analysis and SOAP notes that assist in formulating a management plan.

13 Health Care Processes and Decision Making References – Lecture dGawande, A. (2002). Complications: A surgeon’s notes on an imperfect science. New York: Metropolitan Books. HealthIT.gov. (2013). Shared decision making. Retrieved from https://www.healthit.gov/sites/default/files/nlc_shared_decision_making_fact_sheet.pdf Lenert, L., Dunlea, R., Del Fiol, G., & Hall, L. K. (2014) . A model to support shared decision making in electronic health records systems. Medical Decision Making 34 (8): 987–995. Lown, B., & Rodriguez, D. (2012). Commentary: Lost in translation? How electronic health records structure communication, relationships, and meaning. Academic Medicine 87 (4): 392–394. Weed, L. L. (1968). Medical records that guide and teach. New England Journal of Medicine. Retrieved from Wikipedia (2011). Decision analysis. Retrieved from No audio. Charts, Tables, Figures 4.8 Figure: The complex and dynamic processes that are in play when a patient care problem has to be translated into problem management by the clinician. Mohan, V. (2010). 4.9 Chart: Decision analysis chart. Mills (1991) Retrieved from the National Library of Medicine website 4.10 Figure: SOAP Process Model. By CAST, CC-BY. 4.11 Table: Evolving Management Plan. Mohan, V. (2010).

14 The Culture of Health Care Health Care Processes and Decision Making Lecture dThis material was developed by Oregon Health & Science University, funded by the Department of Health and Human Services, Office of the National Coordinator for Health Information Technology under Award Number IU24OC This material was updated in 2016 by Bellevue College under Award Number 90WT0002. No audio. Health IT Workforce Curriculum Version 4.0