Difference between revisions of "Evaluation of effectiveness and cost-effectiveness of a clinical decision support system in managing hypertension in resource constrained primary health care settings: results from a cluster randomized trial"

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== Background ==
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== Introduction ==
  
There have been many [http://www.texasheart.org/HIC/Topics/Meds/blodmeds.cfm/'''anticoagulant'''], besides [[Reducing warfarin medication interactions | Warfarin (which has many negative interactions)]] such as apixaban, dabigatran, and rivaroxaban that have been introduced and accepted as effective treatment options to prevent and treat stroke and systemic embolism patients. All of these therapy alternatives have their own risks as well as unique benefits and it can be difficult for clinicians to pick the best one for each specific patient's circumstance. In order to help mitigate this issue, a clinical decision aid was created to help prescribing clinicians choose the best type of coagulation therapy by comparing the available treatment options with a particular patient's  individual factors such as risk values and bleeding ratio.
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In the western world, Clinical Decision Support (CDS) has proved to be successful in helping doctors treating and managing hypertension (HTN) patients, however there is not much information on how effective a CDS system would be in a developing country. India is currently experiencing a strong need for more providers in the Primary Health Care (PHC) setting and are also experiencing an increase in healthcare IT available. Therefore there is a chance to get some more insight of how effective CDS could be in lower-income countries at aiding in managing hypertension.  
  
 
== Methods ==
 
== Methods ==
 
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PHC physicians in India were randomized to receive the Decision Support System (DSS) or Chart-based Support (CBS).
The authors gathered national medical claims data for patients diagnosed with AF, who had two or more healthcare encounters that were at least thirty days apart between 2005 and June 2010. These patients were divided into two subgroups - those on commercial health insurance plans, and those on medicare Advantage with part D coverage. All of the patients' HAS-BLED and CHA2DS2-VASc stroke risk score was calculated with the information from the claims and the percentage distribution of each possible combination of HAS-BLED and CHA2DS2-VASc scores was created and each combination's clinical decision aid recommendation was recorded using a baseline bleeding ratio of 2:1. The percentage of the patients that would be recommended to use each choice of anticoagulant was calculated.
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The Decision Support System (DSS) is a software that was previously created to help physicians evaluate and classify their patient’s risk factors of developing Cardiovascular disease, calculate and provide drug-management guidelines and alert the physician to counsel the patient on behavioral changes.  
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The Chart-based Support (CBS) is the same guidelines as those integrated in the DSS software, but printed on a poster and hung where the physician met with his/her patients.
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The DSS and CBS Physicians’ patients who gave consent, were between 35 to 64 years old and had a systolic blood pressure (SBP) of 140+ mm HG and/or diastolic blood pressure (DBP) of 90+ mm HG were included in this study. The both sets of participants’ data was collected and the SBP at 0 and 12 months were compared.
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In order to calculate both the DSS’s and the CBS’s cost-effectiveness, the authors used Drummond’s 10-point check list.
  
 
== Results ==
 
== Results ==
 
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According to the authors’ results, the physicians using the DSS agreed with the DSS suggestions 93% of the time during the study.
The study's findings suggested that there was a strong positive correlation between HAS-BLED and CHA2DS2-VASc scores. Both the mean HAS-BLED and CHA2DS2-VASc stroke risk scores were higher in the sample of patients with Medicare Advantage with part D coverage than the sample with commercial insurance plans.
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The unadjusted mean SBP for the DSS group was calculated for both groups at 0 months and 12 months:
 
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DSS Group 0 months: 151.1                        CBS Group 0 Months: 148.2
If the Clinical Decision Aid chose the treatment for the total sample population the distribution of recommended therapies would be:
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DSS Group 12 Months: 139.9                      CBS Group 12 Months: 144.7
 
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The unadjusted mean DBP for the DSS group was calculated for both groups at 0 months and 12 months:
70.50% apixaban
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DSS Group 0 months: 89.7                        CBS Group 0 Months: 88.4
25.86% no treatment
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DSS Group 12 Months: 84.3                      CBS Group 12 Months: 86.3
3.62% ASA
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The cost-effectiveness ratio (CER) for the DSS group was $36.57 per mm reduction in SBP and the CER for the CBS group was $96.01 per mm reduction in SBP. 
0.01% dabigatran 150
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ASA + clopidogrel, dabigatran 110, and rivaroxaban would not have been recommended by the clinical decision aid for any of these patients.
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== Discussion ==
 
== Discussion ==
 
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A significant improvement was seen in the DSS group for both the unadjusted mean SBP, but the improvement for the CBS group was less significant. This improvement is more significant than previous DSS studies and the authors attribute this to the shortage of providers in PHC settings and specialization of the DSS.  
The clinical decision aid generates recommends therapies based on risks for stroke and major bleeding (which together create the net clinical outcome). The clinical decision aid uses the findings of several anticoagulation medication trial studies to help calculate which therapy would be best for people with various risk factors. This and other evidence-based tools can help physicians when many treatment options are available but many risk and benefit factors go into selecting the best option for a specific patient. With the availability of a relative abundance of new antithrombotic agents this has created a knowledge gap between reasearch and clinical practice. There still exists a great deal of indecision among clinical experts and between organizations and jurisidictions.<ref name="clinical decision aid for antithrombotic therapy">A clinical decision aid for the selection of antithrombotic therapy for the prevention of stroke due to atrial fibrillation.http://eurheartj.oxfordjournals.org/content/33/17/2163</ref>
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== Commentary ==
 
== Commentary ==
  
In this article, the authors point out that this also might be helpful to not only physicians and healthcare providers, but also to healthcare plan payers for population-level patient care optimization which I think is a very interesting point. Since, such a high majority of patients would have been recommended to try apixaban, I'm not sure how this aid would be so important. This seems to me that the majority of patients would be prescribed apixaban and special cases would be more fully analyzed by a patient's care team to determine the be st solution.  
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In this article, the authors wanted to shed some light on the effectiveness of a CDS system in low to middle income countries. While I think this is interesting, this study only included one country’s result and I would caution not to base all low-middle income countries on these results.  
 
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== References ==
 
== References ==
 
<references/>
 
<references/>

Revision as of 00:24, 6 March 2015

This is a review for Raghupathy Anchala, MD, PhD, Stephen Kaptoge, PhD, Hira Pant, MA, Emanuele Di Angelantonio, MD, PhD, Oscar H. Franco, MD, PhD, and D. Prabhakaran's, MD, DM, MSc Creating Evaluation of effectiveness and cost-effectiveness of a clinical decision support system in managing hypertension in resource constrained primary health care settings: results from a cluster randomized trial.[1]


Introduction

In the western world, Clinical Decision Support (CDS) has proved to be successful in helping doctors treating and managing hypertension (HTN) patients, however there is not much information on how effective a CDS system would be in a developing country. India is currently experiencing a strong need for more providers in the Primary Health Care (PHC) setting and are also experiencing an increase in healthcare IT available. Therefore there is a chance to get some more insight of how effective CDS could be in lower-income countries at aiding in managing hypertension.

Methods

PHC physicians in India were randomized to receive the Decision Support System (DSS) or Chart-based Support (CBS). The Decision Support System (DSS) is a software that was previously created to help physicians evaluate and classify their patient’s risk factors of developing Cardiovascular disease, calculate and provide drug-management guidelines and alert the physician to counsel the patient on behavioral changes. The Chart-based Support (CBS) is the same guidelines as those integrated in the DSS software, but printed on a poster and hung where the physician met with his/her patients. The DSS and CBS Physicians’ patients who gave consent, were between 35 to 64 years old and had a systolic blood pressure (SBP) of 140+ mm HG and/or diastolic blood pressure (DBP) of 90+ mm HG were included in this study. The both sets of participants’ data was collected and the SBP at 0 and 12 months were compared. In order to calculate both the DSS’s and the CBS’s cost-effectiveness, the authors used Drummond’s 10-point check list.

Results

According to the authors’ results, the physicians using the DSS agreed with the DSS suggestions 93% of the time during the study. The unadjusted mean SBP for the DSS group was calculated for both groups at 0 months and 12 months: DSS Group 0 months: 151.1 CBS Group 0 Months: 148.2 DSS Group 12 Months: 139.9 CBS Group 12 Months: 144.7 The unadjusted mean DBP for the DSS group was calculated for both groups at 0 months and 12 months: DSS Group 0 months: 89.7 CBS Group 0 Months: 88.4 DSS Group 12 Months: 84.3 CBS Group 12 Months: 86.3 The cost-effectiveness ratio (CER) for the DSS group was $36.57 per mm reduction in SBP and the CER for the CBS group was $96.01 per mm reduction in SBP.

Discussion

A significant improvement was seen in the DSS group for both the unadjusted mean SBP, but the improvement for the CBS group was less significant. This improvement is more significant than previous DSS studies and the authors attribute this to the shortage of providers in PHC settings and specialization of the DSS.

Commentary

In this article, the authors wanted to shed some light on the effectiveness of a CDS system in low to middle income countries. While I think this is interesting, this study only included one country’s result and I would caution not to base all low-middle income countries on these results.

References

  1. Raghupathy Anchala, MD, PhD, Stephen Kaptoge, PhD, Hira Pant, MA, Emanuele Di Angelantonio, MD, PhD, Oscar H. Franco, MD, PhD, and D. Prabhakaran's, MD, DM, MSc Creating Evaluation of effectiveness and cost-effectiveness of a clinical decision support system in managing hypertension in resource constrained primary health care settings: results from a cluster randomized trial. J Am Heart Assoc. 2015 Jan 5;4(1):e001213. doi: 10.1161/JAHA.114.001213. http://www.ncbi.nlm.nih.gov/pubmed/25559011