Employers will always look favourably on the efforts taken by go getters who have gone out and done work experience. Work experience or volunteering is a great way to network and exposes you to a range of core workplace activities, including teamwork, communication skills and how to use your initiative. If I could give my year-old self any piece of advice over and over again it would be not to be scared of rejection.
Getting job rejections can be emotionally difficult and frustrating but it can also be a useful springboard to reassess your goals. There are many different pathways to get to the same destination. You can look at alternative pathways. When I left school I thought that was the end of homework. How wrong I was. And with all that in mind, I wish you good luck for the rest of your adventures in this little thing we call life!
Low pay, earnings mobility and policy — Manchester, Lancashire. Edition: Available editions United Kingdom. Tim Whalley , University of Stirling. Doing the exam jump. Dear class of , Finishing school can be a daunting experience but you are young, bright and have your future ahead of you — easy for me to say, you might think. Yeh, I got this. One trial  evaluated the effect of appointment reminder by mobile phone call compared with a control group that received no reminder and showed a statistically significant increase in attendance RR 1.
Forest plots of the effect of SMS reminders on appointments. Secondary outcomes were as follows: One trial  reported statistically significant reductions in mean time to communicating the diagnosis to the patient and the mean time from test to treatment, but no effects on mean time from first contact to treatment Table We identified 42 controlled trials that investigated mobile technology-based interventions designed to improve health care service delivery processes.
None of the trials were of high quality and nearly all were undertaken in high-income countries. Thirty-two of the trials tested interventions directed at health care providers. Of these trials, seven investigated interventions providing health care provider education, 18 investigated interventions supporting clinical diagnosis and treatment, and seven investigated interventions to facilitate communication between health care providers.
None of the trials reported any objective clinical outcome, and the reported results for health care provider support interventions are mixed. There may be modest benefits in outcomes regarding correct clinical diagnosis and management delivered via application software, but there were mixed results for medical process outcomes regarding the time taken and completeness of or errors in reports or warning scores.
For educational interventions for health care providers, there was no clear evidence of benefit.
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For interventions aiming to enhance communication between health care providers, one trial showed benefits in using the telephone functions of a mobile phone to enhance verbal communication between surgeons and nurses. Two trials showed reductions in the quality of clinical assessment using mobile technology based photos when compared to a gold standard and one trial reported a reduction in quality of ECG print outs delivered via mobile phones. For the category of communication between health services and consumers, SMS reminders have modest benefits in increasing clinic attendance and appear similar in their effects to other forms of reminder.
One trial  reported mixed results relating to time to treatment using SMS to notify patients of their test results. To our knowledge, this is the first comprehensive systematic review of trials of all mobile technology interventions delivered to health care providers and for health services support to improve health or health services.
We identified more than twice the number of trials of educational interventions and trials of PDA applications identified in previous reviews  , . Our review findings are consistent with those of Krishna et al. Our systematic review was broad in its scope. We only pooled outcomes where the intervention function e. Here, findings in relation to clinical diagnosis and management and educational interventions are summarised, the individual trial results are reported in Tables 1 — It was not appropriate to pool these results as the interventions targeted different diseases and outcomes.
Further, there are likely to be important differences in the intervention content of these interventions such as the behaviour change techniques used , even in those using the same mobile technology functions such as application software. It was not possible to explore how different intervention components influenced outcomes as the intervention components were not described consistently or in detail in the authors' papers. It was not possible to explore how the intervention components targeting the disease and outcomes influenced the results.
It was beyond the scope of our review to review internet or video-based interventions not specifically designed for mobile technologies. We also excluded interventions combining mobile technologies with other interventions such as face-to-face counselling, which should be subject to a separate systematic review. Factors influencing heterogeneity of effect estimates include low trial quality, in particular inadequate allocation concealment  , participant factors such as demographics or disease status, the setting hospital, primary care , the intervention features components, intensity, timing , the type of mobile technology device e.
We were unable to statistically explore factors influencing heterogeneity because there were few trials of similar interventions reporting the same outcomes, resulting in limited power for such analyses. It was not possible to statistically explore the mechanism of action of the interventions because there were too few similar interventions reporting the same outcomes.
In addition, authors' descriptions of interventions were insufficiently detailed to allow mechanisms of action to be explored. It was outside the scope of this review to explore the cost-effectiveness of interventions with modest benefits such as appointment reminders. At the request of the editors we re-ran our search on 1 November to any identify other trials eligible for this review published since our last search, and we identified eight trials. One high quality trial demonstrated that text message reminders increased Kenyan health workers' adherence to malaria treatment guidelines with improvements in artemether-lumefantrine management of Three trials reported statistically significant increases in clinic attendance with text message reminders OR 1.
These findings are similar to those reported in trials already included in the review  — . One trial reported statistically significantly increased attendance with voice reminders compared to text message reminders . One trial showed no effect on HIV viral load of a mobile phone-based AIDS care support intervention for community-based peer health workers . One trial reported better performance in a cardiac arrest simulation for health care providers allocated to receiving a mobile phone application regarding advanced life support .
Trials of heath care provider support show some promising results for clinical management, appropriate testing, referral, screening, diagnosis, treatment, and triage. However, trials included in our review were subject to high or unclear risk of bias. In particular, only one of the 17 trials clearly reported that allocation was concealed and where there is no allocation concealment, the reported results may be an over-estimate of effects. To date no trials have reported effects of mobile technology-based clinical diagnosis and management support on objective health outcomes.
Most of the trials supporting health care providers in clinical diagnosis and management employed PDA devices and customised application software functions. While PDA devices are no longer widely used, customised application software functions are now deliverable on smart phones or tablets. Mobile technology-based interventions may not be suitable for some clinical processes. The data available for making clinical diagnoses or calculating early warning scores may be reduced and the time taken for medical processes may be increased.
There was no clear evidence of benefit of mobile technology-based educational interventions for health care professionals. For interventions using mobile technologies to communicate visual data, there were increases in time to diagnosis or ECG transmission or diagnostic errors. Two trials using photos taken by mobile phone reduced diagnostic accuracy of fractures, skin ecchymoses, and potential to perform re-implantation when compared to a gold standard.
However, the use of such technologies may be more relevant for settings where the gold standard is not available. Furthermore, the quality of photos on mobile phones has improved since these studies were completed. Mobile technology-based diagnosis and management support may be most relevant to health care providers in developing countries where mobile phones potentially allow clinical support and evidence-based guidance to be delivered to health care professionals working remotely and in circumstances where senior health care professional support or other infrastructure is lacking .
SMS messages are modestly effective as appointment reminders. Their effects appear similar to other forms of reminder. Health care providers should consider implementing SMS appointment reminders because the cost of missed appointments in health services is high, the cost of providing SMS appointment reminders is low, and SMS reminders are cheaper than other forms of reminder e.
The effects of such support on the management of different diseases and on objective disease outcomes should be evaluated. It is imperative that future trials of clinical decision support, guidance, and protocol delivered via mobile technologies take place in low- and middle-income countries. Many of the interventions evaluated to date are single component interventions of low intensity.
The effects of higher intensity multi-component mobile technology interventions should be evaluated. Authors must describe the components of future interventions in detail so that mechanisms of action and the impact of different components on outcome can be explored. Trials should evaluate the effects of the use of photographic or video functions to support health care providers compared to standard care where gold standard options are not available.
As the technological capabilities of mobile phones improve, such as in photographic quality, further trials of the effects of using photos taken on mobile technologies on diagnostic accuracy may be a warranted. Further research should evaluate the effects and cost-effectiveness of mobile technologies to increase the speed of communication between clinicians and patients, such as test results.
Interventions combining elements delivered by mobile technology with other treatments such as clinics based counselling combined with text messages should be systematically reviewed. The reported effects of health care provider support interventions are mixed. Trials report modest benefits for clinical diagnosis and management support outcomes. For interventions for health services, SMS reminders have modest benefits on attendance. Service providers should consider implementing SMS appointment reminders. One high quality trial published since our literature search was completed shows benefits in adherence to malaria treatment guidelines .
In other areas, high quality trials are needed to robustly establish the effects of optimised mobile health care provider interventions on clinically important outcomes in the long term. Analyzed the data: LW. Wrote the first draft of the manuscript: CF. Abstract Background Mobile health interventions could have beneficial effects on health care delivery processes. Conclusions The results for health care provider support interventions on diagnosis and management outcomes are generally consistent with modest benefits.
Please see later in the article for the Editors' Summary. Why Was This Study Done? What Did the Researchers Do and Find? What Do These Findings Mean?
Introduction Mobile health, the use of mobile computing and communication technologies in health care and public health, is a rapidly expanding area within e-health. Methods We adhered to our published plan of investigation as outlined in the study protocol . Results The combined search strategies identified 26, electronic records; these were screened for eligibility, and the full texts of potentially eligible reports were obtained for further assessment Figure 1.
Download: PPT. Characteristics of Studies Heath care provider support. Table 2. Interventions applied for clinical diagnosis and management.
Table 3. Interventions applied for communication to or between health care providers. Communication between health care services and health care consumers. Table 4. Interventions applied for health services support: appointment reminders. Table 5. Interventions applied for health services support: test result notification.
Interventions The interventions are described according to the authors' descriptions in Tables 1 — 5. Health care provider support. Communication between health services and consumers. Outcomes Health care provider support. Study Quality Health care provider support. Table 6. Cochrane risk of bias summary for health care provider support trials. Table 7. Cochrane risk of bias summary for health service support trials.
Effects We report the effect estimates for primary outcomes and a summary of the effect estimates for secondary outcomes see Tables 8 — 12 for the secondary outcome effect estimates. Table 8. Effect estimates for trials of medical education interventions. Table 9. Effect estimates for trials of clinical diagnosis and management support: appropriate management outcomes testing, referrals, screening, diagnosis, treatment, or triage.
Table Effect estimates for trials of clinical diagnosis and management support: medical process outcomes. Health care provider support No studies reported our primary outcomes. The following secondary outcomes were reported. Discussion Key Findings We identified 42 controlled trials that investigated mobile technology-based interventions designed to improve health care service delivery processes. Strengths and Limitations of the Review To our knowledge, this is the first comprehensive systematic review of trials of all mobile technology interventions delivered to health care providers and for health services support to improve health or health services.
Meaning of the Study, Mechanisms of Action, Implications for Health Care Providers, or Policy Trials of heath care provider support show some promising results for clinical management, appropriate testing, referral, screening, diagnosis, treatment, and triage. Conclusion The reported effects of health care provider support interventions are mixed. Globally, CEA is being used to set public policies regarding the use of pharmaceutical products national formularies in countries such as Australia, 35 New Zealand, and Canada.
Which ratio is the right ratio to use in pharmacoeconomic analyses? ACER reflects the cost per benefit of a new strategy independent of other alternatives, whereas ICER reveals the cost per unit of benefit of switching from one treatment strategy that already may be in place to another. Pharmacoeconomists sometimes want to include a measure of patient preference or quality of life when comparing competing treatment alternatives. CUA can compare cost, quality, and the quantity of patient-years. Cost is measured in dollars, and therapeutic outcome is measured in patient-weighted utilities rather than in physical units.
Often the utility measurement used is a quality-adjusted life year QALY gained. Most often this ratio is translated as the cost per QALY gained or some other health-state utility measurement. QALYs represent the number of full years at full health that are valued equivalently to the number of years as experienced. For example, a full year of health in a disease-free patient would equal 1. CUA is the most appropriate method to use when comparing programs and treatment alternatives that are life extending with serious side effects e.
CUA is employed less frequently than other economic evaluation methods because of a lack of agreement on measuring utilities, difficulty comparing QALYs across patients and populations, and difficulty quantifying patient preferences. Because QALYs and other utility measures are highly subjective, there is some disapreement among researchers regarding which scales should be preferred for measuring utility.
Pharmacoeconomic evaluations also may focus on humanistic concerns. Methods for evaluating the impact of disease and treatment of disease on a patient's HRQOL, patient preferences, and patient satisfaction are all growing in popularity and application to pharmacotherapy decisions.
These methods also can assist clinicians in quantifying the value of pharmaceuticals.
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HRQOL has been defined as the assessment of the functional effects of illness and its consequent therapy as perceived by the patient. Many questionnaires are available, and most are either disease-specific or generic measures of health status. Healthcare practitioners, regardless of practice setting, can benefit from applying the principles and methods of pharmacoeconomics to their daily practice settings. Applied pharmacoeconomics is defined as putting pharmacoeconomic principles, methods, and theories into practice to quantify the value of pharmacy products and pharmaceutical care services used in real-world environments.
Today's practitioners increasingly are required to justify the value of the products and services they provide. Applied pharmacoeconomics can provide the means or tools for this valuation. One of the primary applications of pharmacoeconomics in clinical practice today is to aid clinical and policy decision making. Through the appropriate application of pharmacoeconomics, practitioners and administrators can make better, more informed decisions regarding the products and services they provide. Complete pharmacotherapy decisions should contain assessments of three basic outcome areas whenever appropriate: economic, clinical, and humanistic outcomes ECHO.
Traditionally, most drug therapy decisions were based solely on the clinical outcomes e. Over the past 20 years, it has become quite popular also to include an assessment of the economic outcomes associated with a treatment alternative. The current trend is also to incorporate the humanistic outcomes associated with a treatment alternative, that is, to bring the patient back into this decision-making equation. This ECHO model for medical decision making has become prevalent in current healthcare settings.
Thus, through the appropriate application of pharmacoeconomic principles and methods, incorporating these three critical components into clinical decisions can be accomplished. Pharmacoeconomic data can be a powerful tool to support various clinical decisions, ranging from the level of the patient to the level of an entire healthcare system. Figure 1—2 shows various decisions that can be supported using pharmacoeconomics, including effective formulary management, individual patient treatment, medication policy, and resource allocation.
Decisions for pharmacoeconomic applications. Historically, pharmacoeconomic principles and methods have been applied commonly to assist clinicians and practitioners in making more informed and complete decisions regarding drug therapy. For example, pharmacoeconomics can provide critical cost-effectiveness data to support the addition or deletion of a drug to or from a hospital or MCO formulary, with or without restriction.
In fact, the pharmacoeconomic assessment of formulary actions is becoming a standardized part of many pharmacy and therapeutic committees. Selecting the most cost-effective drugs for an organizational formulary is important. However, it is equally important to determine the most appropriate way to use and prescribe these agents.
Hence, developing and implementing appropriate-use guidelines or policies based on sound pharmacoeconomic data can have a great impact on influencing prescribing patterns. The application of pharmacoeconomics also can be useful for making a decision about an individual patient's therapy. Evaluating the impact a drug has on a patient's HRQOL can be useful when deciding between two agents for customizing a patient's pharmacotherapy.
Although this can be one of the most difficult applications of pharmacoeconomics, it is also one of the most important. The most recent application of pharmacoeconomic principles and methods has been for justifying the value of various healthcare services, particularly pharmacy services. When a specific service is competing for hospital or MCO resources, pharmacoeconomics can provide the data necessary to show that the service maximizes the resources allocated by healthcare system administrators.
Practitioners and administrators can then use these data to make more informed resource-allocation decisions. For example, suppose you want to implement a pharmacy-based therapeutic drug monitoring program. It is hypothesized that this service will improve quality of patient care and save money for the healthcare system.
After negotiating with hospital administrators, the funding for this service is approved for a 1-year trial basis, after which you must document and justify the value of this practice. Theoretically, all the relevant costs and benefits of the program should be measured and, if appropriate, converted into dollars using CBA. Potential benefits can include decreased total drug costs and decreased incidence of ADRs. Potential program costs are primarily the salary and benefits for a pharmacist and additional laboratory tests to monitor patients.
Data documenting that the benefit of this pharmacy service yields a high return on investment ROI should increase the probability of the program continuing to be funded by the healthcare system. Unfortunately, previous reviews of the literature have revealed a disappointing number of rigorous economic evaluations of clinical pharmacy services published to date. In , Schumock and associates 48 reviewed economic evaluations of pharmacy services published between and Despite the relatively low number of methodologically sound studies, this review also revealed some results that demonstrate the potential value of clinical pharmacy services.
Of the studies evaluated, the various clinical services reviewed in this study yielded an average C:B ratio of In , these authors updated their review and included articles published from to For the studies reporting the statistic, B:C ratios ranged from 1. Various strategies are available to incorporate pharmacoeconomics into pharmacotherapy.
Popular strategies for applying pharmacoeconomics to assess the value of pharmaceutical products and services include using the results of published pharmacoeconomic studies, building economic models, and conducting pharmacoeconomic research. Reluctance of decision makers to accept results. Quantifying the value of pharmaceuticals through pharmacoeconomics has increased in popularity.
Many pharmacoeconomic analyses are published in primary medical and pharmacy literature sources. Over the past 30 or more years, the actual number of pharmacoeconomic studies published exceeded 35, in However, the eagerness to conduct pharmacoeconomic evaluations of drugs often exceeds the quality of these evaluations.
Variations in quality and indiscriminate use of pharmacoeconomic terminology are documented in medical and pharmacy literature sources. Therefore, prior to using pharmacoeconomic data to make clinical and policy decisions, decision makers should recognize the potential limitations of those data. A primary consideration when evaluating and interpreting a study is the ability to generalize or transfer the results to other healthcare settings and countries. It can be difficult to generalize and transfer the results of a published study, primarily because of wide variations in practice patterns, patient populations, and costs among healthcare systems and countries.
Further, differences in study perspectives, data sources, and analytic styles may present a challenge for practitioners attempting to extrapolate or relate exact cost savings or cost ratios to their own practice settings.
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To enhance the ability to use pharmacoeconomic results published in the literature, consider the following points:. What is the technical merit of the study? Are the results applicable to local decision making? Do the results apply generally in different jurisdictions with different perspectives? Various guidelines, criteria, reviews, and consensus-based recommendations for evaluating, conducting, and reporting pharmacoeconomic literature have been published.
Each evaluation criterion is briefly discussed next. What is the question s being considered? Is the question clear, defined, and measurable? Is the perspective appropriate given the scope of the problem? Is the evaluation suitable if carried out in a clinical trial? Were all appropriate alternatives considered and described? Were any appropriate alternatives omitted?
Are the alternatives relevant to the perspective and clinical nature of the study? Is there evidence that the alternatives' effectiveness has been established? What are the costs and consequences outcomes included? Are the costs and outcomes relevant to the perspective chosen?
Do they include negative outcomes failures, ADRs? Were costs and consequences measured in the appropriate physical units? Were costs and consequences that occur in the future discounted to their present value? Was any justification given for the discount rate used? Are the results accurate and practical for medical decision makers? Were the appropriate statistical analyses performed? Are the cost ranges for significant variables tested for sensitivity? Are the appropriate and relevant variables varied?
Do the findings follow the anticipated trend? Are the conclusions of the study justified? Is it possible to extrapolate the conclusions to daily clinical practice? Was there any bias due to the sponsorship of the study? A clear statement of the purpose of the study should be given. This objective should be clear, concise, well-defined, and measurable. The researcher must select one or more perspectives e. An evaluation can be conducted from single or multiple perspectives so long as the costs and consequences identified are relevant to the perspective s chosen.
Also, a researcher can claim that a specific method was employed e. Pharmacoeconomic evaluations can be prospective or retrospective. Although prospective designs usually are preferred, retrospective evaluations can be rich with information and reflective of usual care. Many pharmacoeconomic evaluations today are conducted as a part of randomized, controlled clinical trials.
Two cautions for interpreting pharmacoeconomic data collected in this manner include 1 costs can be protocol driven, not necessarily reflective of using a drug in common practice, 65 and 2 control of subjects and decreased complications can yield greater costs and benefits than those observed in common practice.
All relevant treatment options that are available should be described completely or mentioned. The treatment alternatives and dosages being compared should be those used in common practice, and evidence of their effectiveness should be established. Because pharmacoeconomic methods are tools to aid in choosing among treatment alternatives, assessing the cost of a single alternative is considered a partial economic evaluation.
All the important and relevant costs and consequences for each program or treatment alternative should be identified. The costs and consequences identified must be relevant to the study perspective s and measured in suitable terms using the appropriate physical units. Costs should include direct, indirect, and intangible costs. Consequences should include the positive and negative clinical and humanistic outcomes associated with the program or treatment alternative. All these costs and consequences must be valued credibly, with the data sources clearly identified.
The comparison of programs or treatment alternatives should be made at one point in time; thus any costs and consequences not occurring in the present must be addressed. Discounting , or adjusting for differential timing, is the process of reducing any costs and consequences that may occur in the future back to their present value. If a study is performed over time more than 1 year , or if future cost savings are projected, discounting should be done using an appropriate discount rate. Researchers often disagree about which discount rate to use, as well as about whether to discount costs and health benefits simultaneously using the same discount rate s.
A full discussion of the study assumptions and limitations and how to interpret the results in the context of different practice settings 17 should be provided. This discussion should include all relevant issues of concern to potential users of the study. The results should show that the appropriate statistical analyses were performed. Also, it may be appropriate to express the study results in terms of increases, that is, to use incremental cost analysis additional cost of gaining an additional benefit by using one drug over another.
It is imperative that researchers test the sensitivity of study results using sensitivity analysis. Using this method, practitioners and researchers can deal with data uncertainties and assumptions and their effect on study conclusions. Sensitivity analysis SA is the process of testing the robustness of an economic evaluation by examining changes in results.
Specific variables such as percent effectiveness, incidence of ADRs, and dominant resources can be varied over a range of plausible values and the results recalculated. The four general approaches to SA are simple SA, threshold analysis, analysis of extremes, and Monte Carlo simulation analysis.
Researchers should assist the reader in extrapolating study conclusions to clinical practice. The conclusions drawn from the study results should be justified internal validity and able to be generalized external validity. Similar to evaluating the quality of a clinical trial, sponsorship of a pharmacoeconomic study should be considered when evaluating the quality and usefulness of that study.
For example, many of the studies sponsored or conducted by the pharmaceutical industry to date have been academically rigorous as well as informative. A clear understanding of how to evaluate, critique, and use the pharmacoeconomic literature appropriately will minimize any potential effects of this criterion on clinical decision making. Over the years, the literature has highlighted the misuse of pharmacoeconomic terms, inconsistent reporting, and disagreement on the methods used for pharmacoeconomic analyses.
Because pharmacoeconomics is still a fairly new discipline that lacks strong consensus with respect to its methods and technically appropriate applications, the disagreement between leading researchers in this field has been widespread and evident. A review of national guidelines for various countries was published and revealed some areas of emerging standarization. Studies that model the economic impact of a pharmaceutical product or service on a defined population are increasing in popularity.
These studies can use data from various sources available within internal and from outside external a specific healthcare organization. Common approaches to modeling are to modify and adapt existing models or to develop a distinct model to answer a specific question. Several of these are discussed below. Because the development and use of pharmacoeconomic models is so prevalent today, a study examined the perceived value and understanding of pharmacoeconomic models by decision makers in MCOs. Furthermore, no single model format was regarded as the most effective type, although many respondents claimed that simple spreadsheet models were the most effective, followed by well-designed, scientifically rigorous regression models.
Typically, economic modeling in today's practice settings employs clinical decision analysis , which has been defined as an explicit, quantitative, and prescriptive approach to choosing among alternative outcomes. A decision tree provides a framework to display graphically primary variables, including treatment options, outcomes associated with those treatment options, and probabilities of the outcomes. The researcher can then algebraically reduce all these factors into a single value, allowing for comparison. Many examples of decision-analytic models are available in the literature, spanning many therapeutic areas, including the treatment of depression, 73 migraine, 74 type 2 diabetes, 75 and community-acquired pneumonia CAP.
However, chronic conditions or diseases such as chronic hepatitis C are difficult to model using simple decision trees for various reasons, including time-dependent clinical outcomes, and thus may require alternate modeling techniques. Markov models are another method of decision analysis that provides an alternative way to arrange the decision process so that clinical outcomes and time-dependent risk changes are managed efficiently. The Markov model is designed to simulate the most important aspects of a disease and can be used to estimate the long-term clinical, humanistic, and economic dimensions of the disease.
Using an economic model can help the clinician to forecast the impact of medication-use decisions on a patient, institution, or healthcare system. Also, as new drugs are marketed that can displace older agents, an economic model can expedite the reappraisal process for formulary management and drug-use policy decisions. These BIMs, typically spreadsheet analyses, can provide a managed care plan with an estimate of future expenditures for drugs that may be added to their formulary.
An example of a BIM for second-line treatment of major depression can be found in the literature. Clinicians may need to conduct a pharmacoeconomic evaluation if there is insufficient literature, if published results cannot be extrapolated to clinical practice, or if building a model is not appropriate. Before conducting a pharmacoeconomic evaluation, clinicians should be familiar with the similarities, differences, and appropriate application of pharmacoeconomic methods discussed earlier in this chapter.
The decision to conduct a local pharmacoeconomic study is not without its own costs. Because both time and monetary resources are consumed by these evaluations, specific pharmacy products and services for pharmacoeconomic evaluation should be targeted. The resources necessary and the type of evaluation conducted will vary depending on the research question and on whether one is conducting a prospective outcomes analysis or a retrospective database analysis. Table 1—5 highlights the advantages and disadvantages of each type of analyses.
Retrospective database studies have become an increasingly important source of outcomes data, especially in today's MCOs. A item checklist was published in to assist decision makers in evaluating the quality of published studies. Less expensive than randomized controlled trials. Difficulty generalizing results to other providers. Variations in database quality among managed care plans. Inconsistent access to pharmacy versus medical claims. Inability to randomize patients to treatment. Conducting pharmacoeconomic research, whether it is prospective or retrospective, in a hospital or managed-care environment can be challenging.
Lack of institutional resources, small sample sizes, difficulty randomizing, inability to compare with placebo, and difficulty generalizing results all may be limitations. For example, when asked to determine and recommend the most cost-effective antihypertensive agent for a formulary management decision, clinicians can lack monetary and time resources to conduct a prospective scientifically rigorous study.
Depending on the question and setting, a clinician may decide to conduct a retrospective database analysis or a prospective study. In fact, many MCOs today conduct pharmacoeconomic outcomes evaluations by employing a retrospective database analysis of pharmacy and medical claims databases. There are numerous examples of these, spanning a variety of therapeutic areas, in the literature today. Conducting a pharmacoeconomic evaluation should be guided by the criteria for quality economic evaluations.
Although some of these steps are similar to the evaluation criteria detailed earlier in this chapter, they will now be discussed briefly in the context of conducting an evaluation. The study team can provide early buy-in and additional resources for a pharmacoeconomic evaluation. Team members vary depending on the analysis but can include representatives from medicine, nursing, pharmacy, hospital administration, and information systems.
Choose a study perspective s most relevant to the problem. For example, if the problem is as listed in step 1, then the perspective of the institution or healthcare system may be most appropriate. Treatment alternatives can include pharmacologic and nonpharmacologic options but should include all clinically relevant alternatives.
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The outcomes identified should include both positive and negative clinical outcomes. Employing the incorrect method can adversely affect medication decisions influencing both cost and quality of care. Placing a monetary value on treatment alternatives and outcomes includes not only drug administration and acquisition costs but also the cost of positive and negative clinical outcomes e. This can be measured prospectively or retrospectively or estimated using comprehensive databases or expert panels.
Resources necessary will vary by study but can include access to medical or computerized records, average medical personnel wages, and specialty medical staff. What are the probabilities of the outcomes identified in step 4 actually occurring in clinical practice? Using primary literature and expert opinion, these probabilities can be obtained and may be manifested as efficacy rates and incidence of ADRs. The use of decision analysis can assist in conducting various economic evaluations, including CEA. Although not necessary for all pharmacoeconomic evaluations, decision analysis and decision trees can provide a solid backbone or platform for the decision at hand.
Using a decision tree, treatment alternatives, outcomes, and probabilities can be presented graphically and can be reduced algebraically to a single value for comparison i. Many of these agents differ with respect to effectiveness, safety, and cost. By performing a thorough CEA, these variables can be reduced to a single number cost-effectiveness ratio , which will allow for a meaningful comparison. The treatment alternative with a better cost-effectiveness ratio than the others i. Figure 1—3 contains an example of a decision tree illustrating how the probabilities of various outcomes can be organized.
Repeat this process for drug B using paths 5 through 8. Example of a pharmacoeconomicdecision tree comparing two drugs. Option B is a drug that is more specific for the target receptor in the body, is more effective, and produces fewer adverse effects than does option A. However, because drug B is more expensive than drug A , the cost of the added benefits must be analyzed using pharmacoeconomic techniques.
This figure was completed using the safety and efficacy values for drugs A and B from Table 1—6. Applied pharmacoeconomics: Modeling data from internal and external sources. Am J Health Syst Pharm ;— Using the values in Table 1—6 , another way to calculate the ACER for these treatment options is to multiply the cumulative probabilities P by the cumulative costs for each path, then sum the costs for each path 1 through 4 for drug A and 5 through 8 for drug B , and then divide by each drug's respective effectiveness for acute CIE.
Costs and consequences that occur in the future must be discounted back to their present value. Sensitive variables must be tested over a clinically relevant range and results recalculated. If appropriate, an incremental analysis of the costs and consequences should be performed. Results should be presented to the cross-functional team and the appropriate committees at an institution or MCO. Presentation style and content can vary depending on the audience. Take the study results and develop a policy or an intervention that can improve or maintain quality of care, possibly at a cost savings.
Spend adequate time and resources strategically implementing the policy or intervention. Educate the healthcare professionals most likely to be affected by this policy using various strategies, including verbal, written, and online communication. Once the intervention or policy has been implemented for a reasonable period of time, collect follow-up data.
These data will provide feedback on the success and quality of the policy or intervention. For additional information and hands-on practice conducting a pharmacoeconomic evaluation in the real world, practitioners should consider a published case study. In , Okamoto published a case study on conducting a pharmacoeconomic evaluation using 16 steps that readers also may find useful. In this case, clinicians are challenged to conduct a faux economic analysis from an MCO provider perspective to support a review of inhaled corticosteroids for formulary management purposes.
The principles and methods of pharmacoeconomics provide the means to quantify the value of pharmacotherapy through balancing costs and outcomes. Providing quality care with minimal resources is the future, and the future is here. By understanding the principles, methods, and application of pharmacoeconomics, healthcare professionals will be prepared to make better, more informed decisions regarding the use of pharmaceutical products and services—that is, decisions that ultimately represent the best interests of the patient, the healthcare system, and society.
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