IPSQWHIT: Measuring the quality improvements associated with decision support in pediatrics AHRQ HIT Conference Timothy G. Ferris, MD, MPH Medical Director, MGPO Associate Professor of Medicine and Pediatrics Harvard Medical School

BACKGROUND Expectations for the ability of EHRs to improve quality are based on potential of decision support Slow adoption is a barrier PaperEHRDS Evidence of improved quality summarized in Shekelle/AHRQ Evidence Report Significant improvements in quality Difficult to aggregate and/or generalize ONC Report on measuring quality benefits of HIT –

IPSQWHIT Improving Patient Safety and Quality With Health Information Technology –Funded by the Agency for Healthcare Research and Quality (AHRQ) HIT Value RFA Focused on improvements in safety, quality, and efficiency through HIT Several pediatric grants funded

IPSQWHIT e-Rx decision support: Weight based dosing Reminders (synchronous and asynchronous) Results management Templates (acute and chronic conditions) All specifications and templates available on AHRQ website

Prioritizing Decision Support MD use of DS has limits –Need to prioritize what is asked of them Grounds for prioritization: –Safety –Clinical impact Evidence for improvement –Common problem/small impact –Rare problem/large impact

Design and Setting Group randomized trials conducted within Partners Healthcare in Eastern MA. 26 pediatric practices –All participants had already adopted the same EHR –Hospital based (1), health center (6), private (19) –Participation depended on multiple factors –Once selected, sites were paired by type and randomized to intervention or control. –Analyses adjusted for clustering by MD and practice

Weight Based Dosing Decision Support

Medication Errors in Pediatrics Medication errors among the most common and most injurious of all errors in health care 1 Pediatric prescriptions may be more prone to error Limited data on rates of pediatric dosing errors Unclear if computerized decision support in the context of electronic prescribing reduces weight related dosing errors 1 Bates DW, et al, JAMA. 1998; Dean B, et al. Qual Saf Health Care. 2002; Kaushal R, et al. JAMA Sullivan JE, et al. J Surg Oncol. 2004

OBJECTIVES To examine the prevalence of dosing errors in ambulatory pediatrics To examine the effectiveness of weight based dosing decision support in reducing the frequency and severity of dosing errors

DESCRIPTION OF INTERVENTION The WBDDS included two components: 1.Active component: a medication menu allowing selection of a dose based on the child’s weight 2.Passive component: display of a computer generated total daily dose in mg/kg based on the child’s weight Child’s most recent weight imported from the EHR

Weight based dosing calculator Active (part 1) Dose calculated based on patient weight Passive: Total daily dose calculated Active (part 2) Select rounded dose from drop-down menu

RESULTS : Dosing errors as a proportion of child office visits n=32942 (100%) n=17526 (53%) n=3684 (11%) n=285 (.87%) n=22 (.06%) All visits All visits where any Rx provided All visits where WBD Rx provided Adverse drug events All visits with a WBD Rx error 7.7% of eligible meds had a dosing error 1% had a dosing error >10% from recommended dose

RESULTS: Rates of dosing errors for weight based dosing medications Control Change in frequency of errors per 100 prescriptions Intervention Change in frequency of errors per 100 prescriptions p All Dosing Errors Overdoses (all) Overdoses (antibiotics) <.0001 Overdoses (other) Under doses (all)

RESULTS: Physicians prescribed antibiotics more than any other type of medication and antibiotics were the most likely medication to include a dosing error The active decision support (WBDDS) was used for approximately 10% of Rx in intervention group –No dosing errors when active decision support was used

RESULTS: Majority of dosing errors (58%) judged to be correctable with use of decision support 22% of dosing errors considered directly attributable to incorrect use of the electronic prescribing software Interviews revealed a number of barriers: technical difficulties, user interface challenges, and negative physician perceptions

LIMITATIONS Prescribing software did not accommodate medications requiring variable dosing or combination medications –Significant source of dosing errors Unable to fully assess physician use No systematic assessment for ADE’s

CONCLUSIONS Dosing errors represent a substantial fraction of medication errors in pediatrics –10% of eligible Rx –National extrapolation: approximately 4,000,000 dosing errors in weight based dosing eligible pediatric prescriptions every year WBDDS reduced dosing errors from 10.0 per 100 scripts to 6.3 per 100 scripts –National extrapolation: reduction of over 150,000 dosing errors per year Real world effectiveness vs. ideal world efficacy

CONCLUSIONS Very few adverse drug events associated with these dosing errors No incorrectly dosed prescriptions when the active form of WBDDS was used Difficulties using software were a major barrier to regular use of the active DS

IMPLICATIONS Weight based dosing decision support led to reductions in the overall dosing error rate and for overdoses in particular New errors caused by electronic prescribing software Full benefit of e-prescribing will require WBDDS designed to accommodate physician workflow

Alerts & Reminders

Reminders ADHD: % of patients receiving follow-up care every 6 months –Rates: 53.9% (Cont) vs. 70.1% (Int) (p=.04) 33.5% vs. 43.7% at ADHD visit (p=.27) 22.3% vs. 28.2% at Well child check (p=.33) –Intervention patients were 2.1 times as likely to have had appropriate follow-up

Reminders Chlamydia: annual screening test for patients who are sexually active –Rates: 24% (Control) vs. 48% (Intervention) –61% of screening tests were ordered by the patient’s PCP

Reminders Obesity: –Lipid profile every 2 years for patients with BMI >99 th percentile 23 of 200 patients (11.5%) received a lipid profile No significant difference between control and intervention (13 intervention vs.10 control) –Follow-up visit every six months patients with BMI >95 th percentile 75% of intervention group patients had visit where nutritional habits were reviewed vs. 71% in the control (p=.5)

Results Management

Main findings: –Full adoption practices reported gains in efficiency, reliability, timeliness, and provider satisfaction –Some partial adopters reported decreased efficiency and increased risk of lost test results –Barriers to ERM adoption included lack of inclusion of all ordered tests in the ERM system, user- interface design issues, and lack of sufficient pediatric customization Ferris et al, Pediatrics (in press)

Templates

ADHD –Usage: 32% of ADHD specific visits at intervention clinics –Documentation quality: Documentation of symptoms: 96.6% (T) vs. 29% Treatment effectiveness: 100% (T) vs. 61.3% Treatment side effects: 96.6% (T) vs. 54.8%

ARI Smart Form Usage: –Successfully used at 561 ARI visits to treat 522 individual patients with 680 primary and secondary diagnoses –The Smart form was employed by 39 providers with a median number of uses/user of 18 (range 1-109) –Used for only 8% of all eligible visits (!)

ARI Smartform Changes in prescribing: –In the intervention group, fewer antimicrobial prescriptions were written when the SF was used: 31.7% (SF) vs. 39.9% (p<.0007) –Providers using the SF were less likely to recommend a macrolide antibiotic 6.2% of ARI visits vs. 9.5%, p=.022 –Providers also prescribed fewer antibiotics for viral ARI illnesses when utilizing the SF 12.3% of viral ARI visits versus 18.1% of viral ARI illnesses; p=.0125)

Lessons learned: Clinical perspective –Outpatient pediatric workflow necessitates tools designed specifically for that population and setting –Clinicians respond with variable frequency to prompts to perform preventive care measures –Reminders promote effective management of chronic conditions at well child visits (well child templates might inhibit documentation) –Smartform lead to increased guideline adherence for acute illness care

Lessons learned: QI/ HIT perspective –Administrative/organizational barriers are substantial –Effective design requires cooperation from practice administrators, IT personnel, network leadership, and clinicians—also iterative modification as guidelines change –Variation in clinical workflow across ambulatory settings necessitates the tools that can be easily modified –Given the impact of perceived value on use, provider training and education appear an integral component of implementation

Acknowledgments AHRQ –Iris Mabry –Jon White Co-Investigators –John Co –James Perrin –David Bates –Rainu Kaushal –Eric Poon Research Assistant –Sarah Johnson