Clinical Decision Support for Population Health. Scott Weingarten
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1 Clinical Decision Support for Population Health Scott Weingarten 1
2 Health Care 2014 Affordability crisis 80% to 90% of costs are from clinical decisions Studies Show Overtreatment subjecting patients to care that, according to sound science and the patients own preferences, cannot possibly help them $248 billion per year 10% of health care expense NEJM 2013;369: Berwick DM, et al. JAMA 2012;307:1513-6
3 Reducing Costs and Improving Quality 75% of decision support interventions succeed when the information is provided to clinicians automatically, whereas none succeed when clinicians are required to seek out the advice Predictors of Success Automatic provision of decision support as part of workflow Provision of decision support at the time and location of decision making Adjusted OR 112 Provision of recommendation rather than just an assessment 7 Computer-based generation of decision support 6 15 Source: Kawamoto K, Houlihan CA, Balas EA, Lobach DF. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ Apr 2;330(7494):765. PMID:
4 What Next? Which is better An error of omission or of commission? A swing and a strike or a called strike? 4
5 What Will Enable Us to Succeed? Population health CDS Increase alert go live rate 50-fold Big bang with alerts Alerts to significantly and safely reduce PMPM Alerts to improve quality 5
6 310 alerts covering 180 Choosing Wisely Recommendations > 58% of Choosing Wisely recommendations through June 2014 content for inpatient and ambulatory settings
7 Patient Education Consumer Reports Choosing Wisely information made available to all physicians to hand to patients My patients demand to have an.. 7
8 Accident Avoidance Systems Lowered accident claims Mercedes 16% Acura 15% 8
9 alert fatigue? alerts 320 per day
10 Choosing Wisely to Prepare for Risk
11 American Geriatric Society 11
12 American Academy of Neurology American Society of Clinical Pathology 12
13 Impact Analysis Pre Intervention Jan 1 Sep 9 Post Intervention Sep 10 Nov 25 mean orders mean orders % change p-value Antipsychotics Patients 70 Benzo-Sedatives Patients 65 Butalbital Adults Vitamin-D levels % < % < % < % <0.001 Rates per 10,000 encounters
14 Avoiding Alert Fatigue? Relationship of PPV versus number of alerts triggered Breakdown of alerts with PPV >=60% by type Confidential 14
15 Deep Dive Increased risk of falls (57% for benzos, 97% for Valium) Increased risk of MVAs Increased risk of hip fractures Arch Intern Med. 2009;169(21): J Am Geriatr Soc 59: ,
16 Impact of Blind Spot Monitor Prescriptions of Benzodiazepines to Elderly Patients Change in number of prescriptions from baseline with active alert* Age >=65 years Age <65 years Pilot MD offices -20.9% 3.6% Control MD offices 10.6% 3.5% Difference -31.5% +0.01% *Comparison periods 7/13/13 to 8/6/13 and 8/7/13 to 8/31/13 16
17 projected reductions over 1 year reduction in benzodiazepine use 22 fall related injuries 6 ED visits 3 hospitalizations potential impact 2 deaths from falls Woolcott et al. JAGS 2009, CDC. MMWR Weekly 2008, Schiller et al., Adv Data No. 392 (CDC) 2007, Pariente et al, Drugs Aging 2008
18 60 Fewer antipsychotics prescribed for dementia on hospital discharge Serious events 6-7 Including* 1 Hospitalization for EPS, stroke, falls/hip fractures 5 Hospitalizations for other causes 1-2 Deaths potential impact in one month * Hospitalization and subsequent death = 1 event Adjusted OR=3.19 to 3.81 for typical and atypical antipsychotics vs no antipsychotics, respectively Sources for projections: Rochon et al. JAMA 2013
19 Savings from Cancelled Orders Only Savings projected from cancelled orders alone immediately following an alert are $1.83 million annually
20 Modified Our Local Conventional Wisdom Could increase CDS go live rate significantly Big bangs with 180 new alerts Physicians did not customize CDS Choosing Wisely is a great brand Migrating to medium stops went fine 20
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