Medical Billing, Emar & Prescription Safety
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1 Medication Quality and Health Information Technology Prescribing CPOE Ajit Appari, Ph.D. Postdoctoral Research Fellow Center for Digital Strategies Tuck School of Business, Dartmouth College Hanover, NH Dispensing emar Administration/ Monitoring Coauthors Dartmouth College] Emily Carian, AB Eric Johnson, PhD Denise Anthony, PhD Partial Funding Support: National Science Foundation [Grant# NSF-CNS ] Rockefeller Center at Dartmouth College June 13, 2011
![03755 Dispensing emar Administration/ Monitoring Coauthors [@ Dartmouth College] Emily Carian, AB Eric Johnson, PhD](/docs-images/57/5646741/images/page_1.jpg "Denise Anthony, PhD Partial Funding Support: National Science Foundation [Grant# NSF-CNS-0910842] Rockefeller Center")
2 Why this study? Gap between postulated and observed linkage remains [See Buntin, et al (2011); Black, et al. (2011); Lau et al. (2010)] Role of health IT in medication management process [AHRQ, April 2011] Primary focus: Physician side IT (Clinical decision support & computerized provider order entry) Rarely examined Nursing side IT 2
3 Research Objective To determine whether use of electronic medication administration record (emar), and computerized physician order entry (CPOE) are associated with better medication quality (context: hospitals). by technology adoption status (Hypothesis-1) i.e. adoption effect. by duration of technology use (Hypothesis-2) i.e. quasi experience effect. 3
4 Study Design Data Sources HIMSS Analytics (December 2010 update) 5281 nonfederal hospitals (acute/ critical) IT adoption censored at 2008 CMS Hospital Compare (September 2010 release) 11 Quality measures during Jan-Dec hospitals (acute/ federal/critical) CMS Acute Inpatient Prospective Payment System 2010 File Select hospital characteristics 3596 acute care hospitals 4
5 Study Design Analytic Sample [2603 hospitals]: Non-federal acute-care hospitals Bed Size>=100 Quality score for at least 25 eligible patients Statistical Analyses: Quality scores are proportion and bounded [0, 1] Generalized linear model (Logit link; Binomial family) Software package: Stata v11.1 Quality = f (health IT; Common hospital characteristics; Past patient volume; Propensity scores for IT adoption) / Error HRR level 5
6 Data Summary emar and CPOE adoption at 2603 hospitals by year 2008 Technology Indicators 69% emar & CPOE: 31% (n=804) 69% 35% 35% CPOE-only: 4% (n=115) Non-adopters: 27% (n=698) n=1790 n=919 emar CPOE emar-only: 38% (n=986) Duration of Use: 2 years increment 6
7 Data Summary (%) Adherence to medication guidelines for AMI patients at 2603 hospitals Quality Measures Mean (SD) Range AMI 1: Given Aspirin at admission 98.7 (1.6) AMI 2: Prescribed Aspirin at discharge 98.7 (2.0) AMI 3: Given ACE Inhibitor or ARB for Left Ventricular Systolic Dysfunction (LVSD) AMI 5: Prescribed beta blocker at discharge 95.9 (4.5) (2.0)
8 Data Summary (%) Adherence to medication guidelines for Heart Failure and Pneumonia patients at 2603 hospitals Quality Measures Mean (SD) Range HF 3: Given ACE Inhibitor or ARB for LVSD 94.7 (5.4) PN 5: Given initial antibiotic(s) within 6 Hours of arrival PN 6: Given most appropriate initial antibiotic(s) 94.9 (4.2) (5.5)
9 Data Summary (%) Adherence to medication guidelines for Surgical patients at 2603 hospitals Quality Measures Mean (SD) Range SCIPINF 1: Received preventive antibiotic within one Hour before incision SCIPINF 2: Received most appropriate antibiotic(s) for surgery SCIPINF 3: Stopped preventive antibiotic(s) within 24 Hours after surgery SCIPVTE 2: Treatment to prevent blood clots within 24 Hours before/after surgery 96.9 (2.8) (2.1) (4.6) (6.4)
10 Results: Hypothesis1 The Adjusted Odds Ratios (95% confidence intervals) for emar and CPOE adoption on medication process quality at medium-to-large acute-care hospitals in US (n=2603) Conditions: Heart Failure Pneumonia 10
11 Results: Hypothesis1 The Adjusted Odds Ratios (95% confidence intervals) for emar and CPOE adoption on medication process quality at medium-to-large acute-care hospitals in US (n=2603) Conditions: Acute MI 11
12 Results: Hypothesis1 The Adjusted Odds Ratios (95% confidence intervals) for emar and CPOE adoption on medication process quality at medium-to-large acute-care hospitals in US (n=2603) Conditions: Surgical Infection Prevention 12
13 Marginal Effects of emar and CPOE Quality Measure None emar-only CPOE-only emar & CPOE Predicted Quality (%) Marginal difference from None (%) AMI1: AMI2: AMI3: AMI5: HF3: PN5: PN6: SCIP-INF1: SCIP-INF2: SCIP-INF3: SCIP-VTE2:
14 (Hypothesis 2) Quality:: Duration of Use Adjusted Odds Ratios (95% CI) for 2 years incremental duration of use 14
15 Summary/Conclusion Technology adopters perform better on 10/11 measures emar-only adopters: Adjusted Odds: 14-29% higher emar & CPOE adopters: Adjusted Odds: 13-38% higher Marginal Effect on quality score: 0.3 to 2.0 percentage points Incremental use of 2 years associated with 6-15% higher Adjusted Odds emar-only adopters AND emar & CPOE adopters emar alone and in combination with CPOE associated with better quality 15
16 What we don t do!! Consideration of variations in Functionality of IT, Associated technologies, e.g. CDS and bar-code Extent of technology use within hospitals Quality comparison before/ after adoption pseudo causal effect 16
17 Questions/ Comments 17
18 Research Model: Schematic View Response Variables Process Performance (2009) Acute Myocardial Infarction [AMI] (4 measures) Heart Failure [HF] [1 measure] Pneumonia [PN] [2 measures] Surgical Infection Prevention/ Improvement [SCIP] [4 measures] Explanatory Variables emar, CPOE (2008) In use duration Adjustments Or Controlled for Teaching Profit status Rural location Multihospital system Qualified for DHS payment Trans. Adj. case mix index Bed size HRR level error clustering Historical measure-specific patient volume ( ) Propensity scores of IT adoption 18
19 Population Studied/ Data Summary 100% Duration of Technology Use 90% 80% 33% 27% 70% 60% 50% 40% 30% 20% 10% 0% 6% 11% 8% 10% 27% 26% 17% 17% 9% 9% emar CPOE Missing >8 Yrs 8 Yrs 6 Yrs 4 yrs 2 Yrs 19
20 Data Summary: Medication Quality Quality Measures [%] All Hospitals EMAR No Yes CPOE No Yes n Mean Mean Mean Mean Mean AMI AMI AMI AMI HF PN PN SCIPINF SCIPINF SCIPINF SCIPVTE AMI1: Given Aspirin at admission; AMI2: Prescribed Aspirin at discharge; AMI3: Given ACE Inhibitor or ARB for LVSD; AMI5: Prescribed beta blocker at discharge; HF3: Given ACE Inhibitor or ARB for LVSD; PN5: Given initial antibiotic(s) within 6 Hours of arrival; PN6: Given most appropriate initial antibiotic(s); SCIPINF1: Received preventive antibiotic within one Hour before incision; SCIPINF2: Received most appropriate antibiotic(s) for surgery; SCIPINF3: Stopped preventive antibiotic(s) within 24 Hours after surgery; SCIPVTE2: Treatment to prevent blood clots within 24 Hours before/after surgery. 20
21 Hospital Characteristics by IT Adoption All hospitals emar hospitals CPOE hospitals Hospital Characteristics [N=2603] n (%) [N=1790] n (%) [N=919] n (%) Teaching 976(37.5) 706(39.4) 451(49.1) For-profit 499(19.1) 310(17.3) 64(7.0) Multihospital health system 1879(72.2) 1331(74.4) 681(74.1) Rural 383(16.3) 239(14.8) 75(9.4) Qualified for disproportionate share payment 1,902(81.1) 1,266(78.6) 612(76.7) Bed Size Category beds 1,009(38.8) 630(35.2) 263(28.6) beds 626(24.1) 448(25.0) 237(25.8) beds 411(15.8) 284(15.9) 148(16.1) 400+ beds 557(21.4) 428(23.9) 271(29.5) Transfer adjusted case mix index* 1.49(0.24) 1.51(0.24) 1.55(0.25) *: mean (SD) are reported 21
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