Safety and Quality of Prescribing by Medical Residents: Implications for

Electronic Prescribing

Darren Triller, Pharm DSenior DirectorHealth Care Quality ImprovementIPRO

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Introduction/ Background• Medication-related problems are major contributors to avoidable morbidity and mortality, and unique environmental and system factors may increase the risk of patients encountering problems with prescriptions originating from academic medical centers and issued by medical residents.

• While emerging electronic prescribing technology has the potential to eliminate some types of prescribing problems, it is unclear whether existing e-prescribing technology has the ability to address problem types most commonly associated with prescriptions issued at large academic medical centers.

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Study Goals

• Quantify & characterize problems identified with prescriptions presented to pharmacies in close proximity to academic medical centers

• Evaluate whether problems are more prevalent with “Resident-issued” prescriptions

• Determine whether existing electronic prescribing technology has the potential to address identified problem types

Methods• The study utilized a technical expert panel (TEP) to develop and test data collection process and tools

•Collected real-time data from a representative sample of pharmacies in close proximity to large academic centers across the state.

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Methods Cont.Using Google Maps®, pharmacies with proximity to the largest academic medical centers were recruited for voluntary participation in the study.

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Methods Cont.

• Pharmacies were approached in descending order of program size and in increasing order of distance from the medical center

• Goal of recruiting 2-3 pharmacies in proximity to each of six targeted residency programs from across the state

• 15 pharmacies were successfully recruited

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Academic Program SizeProgram Size (# of total

residents)Hospital Name Region # of participating

pharmacies

556 Mount Sinai Hospital NYC 3

526 Strong Memorial Hospital Upstate 2

443 New York Presbyterian Hospital (Weill)

NYC 1

381 SUNY University Hospital (Stony Brook)

Long Island 1

333 Maimonides Medical Center

NYC 1

331 Long Island Jewish Medical Center

NYC 1

303 Kings County Hospital Center

NYC 1

219 SVCMC-St. Vincent’s Manhattan

NYC 1

206 *Brooklyn Hospital NYC 1

76 *Metropolitan Hospital NYC 1

60 *Rochester General Hospital

Upstate 2

Methods Cont.•Study staff, trained pharmacists or pharmacy students collected the data. (training video)

• All problems were tracked for 24 hours & then considered “Timed out/ not resolved” if there was no resolution documented by that time.

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Day 1 Day 2 Day 3

Document problems associated with new prescriptions received.

Collect data on resolving problems from day 1 & document problems associated with new prescriptions received.

Collect data on resolving problems from day 2

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Methods Cont.

• A documented “problem” was any instance in which a pharmacist, when presented with a newly issued prescription, could not continue the dispensing process without rectifying some component of the prescription.

• All such instances inherently contribute to delays in medication procurement by the patient, which, in and of themselves, may contribute to adverse outcomes.

Categories of problems associated with prescriptions

Methods Cont.

•Data from participating pharmacies was aggregated and analyzed to quantify the rate of problems and the characteristics of the most common problem types.

•Additional analysis compared rates of problems by prescriber type and intake type.

•The incidence of unsafe prescriptions was assessed via query of clinical members of the TEP using Survey Monkey® for both the clinical impact of the delay in patient care and the potential severity of prescriptions that were identified as clinical problems.

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Results

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Results Cont.

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4.6% of new prescriptions received on study days contained problems. (203 out of 4,452)

Results Cont.

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Rx intake Total Scripts

Problem Scripts

Problem Rate

e-Rx 435 14 3.2%

Faxed 391 36 9.2%

Phoned 926 21 2.2%

Written 2321 132 5.7%

Problem rate by prescription intake

p<0.05

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Results Cont.

p<0.05

Post-Hoc Analysis Rationale

•To determine whether practices within pharmacies (e.g. attributing prescriptions written by residents to their attending physicians) might unintentionally bias the results against residents by deflating the denominator in rate calculations.

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Pharmacy Resident Attending

A 0 270

B 2 121

C 27 330

Original Post-HocResident Attending

26 244

1 122

54 303

7.5% of Attending prescriptions were actually written by Residents

Post-Hoc Analysis Results

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p<0.05

Results Cont.

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Drug Category % of all problemsAntibiotic 11.17%

Narcotic 9.22%

Antidepressant / antipsychotic 5.83%

Proton Pump Inhibitor 5.34%

Steroid 5.34%

Benzodiazepine 3.88%

Statin 3.88%

Supplies (first-aid) 3.40%

Vitamin 3.40%

Beta Blocker 2.91%

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Results Cont.

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Results: Clinical Impact of Delayed Prescriptions

• 25.1% of problem prescriptions “timed-out” (n=51)

• TEP Survey Results:

• 60% considered to be highly likely/likely to cause a worsening or prolongation in symptoms.

• Ex: narcotic pain relievers, antibiotics, topical steroids, antiemetics, etc.

• 20% considered highly likely/likely to cause a worsening or progression in disease state.

•Ex: antibiotics, insulin, antihistamine, etc.

Results: Potential Severity Classification of Clinical Problem Prescriptions

•11.3% of Problems were deemed “clinical” in nature by data collector

•11 of 27 clinical problems were selected to rank their potential severity to the patient assuming the order was filled/taken as originally written.

•TEP Survey Results:

• Four (36.4%) of the cases presented were ranked by the TEP as Potentially Significant.• Ex: Inappropriate dose, Inappropriate quantity, etc.

• Three (27.3%) of the cases presented were ranked by the TEP as Potentially Fatal/Severe.• Ex: Drug-drug interaction, inappropriate dose, severe overdose, etc.

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Impact of E-Prescribing Methods

•The TEP was queried using Survey Monkey® to ascertain the potential ability to diminish or avoid such problems using existing e-rx technology

•asked to review each problem subtype and rank the likelihood that e-rx features could address that problem type•asked to identify specific e-rx applications that presently include the required features•staff evaluated identified applications to verify the availability of necessary features

•The presence of an available feature was then assumed to have the potential to avoid/rectify related problem subtypes. Final summary estimates reflect the percentage of problem prescriptions potentiallty avoidable using e-rx technology.

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Clerical Total (n=100) 41.8%Distribution of Problem Types

% of all Problems Systems Referenced

Electronic feature available & confirmed by vendor (Y/N)

Drug not available/not in stock (In US)

10% Yes Yes

Drug not available/not in stock (In specific pharmacy)

No

Missing/Illegible patient info

7.5% Yes Yes* Interface to PMS $300 or $1500

Missing/Illegible prescription/drug info

7.1% Yes Yes

Missing/Illegible prescriber info

4.2% Yes Yes

Prescription not dated 2.9% Yes Yes

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Insurance Total (n=112) 46.9%

Distribution of Problem Types

% of all Problems Systems Referenced

Electronic feature available & confirmed by vendor (Y/N)

Drug not covered 13% Yes Yes

Invalid Date 10.9% No No

Prior authorization needed

8.8% No Yes

Patient not covered 2.1% Yes Yes

Invalid qty prescribed

2.1% Yes Yes

Patient could not afford

1.7% No Yes* Depending on plan

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Clinical Total (n=27) 11.3%Distribution of Problem Types

% of all Problems Systems Referenced Electronic feature available & confirmed by vendor (Y/N)

Inappropriate QTY 2.9% Yes Yes

Inappropriate Dose 2.5% Yes Yes

Inappropriate Form 1.3% Yes Yes

Drug-drug interaction 1.3% Yes Yes

Inappropriate Frequency 0.8% Yes Yes

Contraindication 0 % Yes Yes

Duplicate Therapy 0.8% Yes

Allergy 0% Yes Yes

Inappropriate Drug for dz/condition

0% Yes Yes

Inappropriate duration 0% Yes Yes

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Result Summary

• Problems with prescriptions are still unacceptably common, and adversely affect patient care• Prescriptions written by residents appear to have a higher rate of problems than other prescribers• E-Prescribing has the potential to reduce 69% of the problems encountered at pharmacies.

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Limitations

• Pharmacy recruitment was difficult, and other pharmacy practices and may have biased or otherwise affected data• Capture of event data on the pharmacy side “diluted” the volume of prescriptions issued by residents.• Despite the large number of total prescriptions involved, the relatively small sample of identified problems limited the ability to analyze potentially contributing variables

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Conclusion

•Prescriptions issued by residents appear to be more prone to problems, suggesting that educational interventions may improve quality.

•Existing e-rx technology has the potential to reduce or eliminate many types of problems, and should be considered for implementation in academic medical center environments as a means of improving quality and safety.

The Project is a part of a state-wide Medication Safety Initiative funded by the New York State Attorney General’s settlement with Cardinal Health, Inc. and administered by Health Research Inc. (HRI)

•Project Assistance: Derik Wandell, PharmDTina Fan, MDTierney Clark, PharmD Candidate

•Special thanks to all participating pharmacies.

Special Acknowledgements

For More InformationProject Director: Darren Triller, Pharm D(518) 426-3300 x125dtriller@nyqio.sdps.org

Project Coordinator: Stephanie Cannoe-Petersen, MA(518) 426-3300 x144scpetersen@ipro.org