Quality and Technology
N9205 Oct. 17, 2000
Columbia University School of Nursing M6920, Fall, 2000
Assessing the quality of care or services
Was the right thing done?
Was it done done right?
Did it yield the right results?
Columbia University School of Nursing M6920, Fall, 2000
Donabedian framework
Structure/input• capital investment• staffing• relationships
Process• content• sequence
Outcome
Columbia University School of Nursing M6920, Fall, 2000
Assessing qualityPerson seeks care
Provider
Case FindingScreeningDiagnosis
Diagnosis
ManagementPatient Education
ReferralsTherapy
MonitoringFollowup
Desired effects Office of Technology
Assessment, 1988
Outreach Activities
Primary Prevention
Evaluation ofPresenting ComplaintHistory,Physical
Other DiagnosticProcedures
Columbia University School of Nursing M6920, Fall, 2000
Critical issues
Selection of domain
Selection of measures
Identification of data source
Columbia University School of Nursing M6920, Fall, 2000
A special case : technology assessment
Generally includes "machines" Would also cover pharmaceuticals? Other possible "hidden"
technologies• scheduling• staffing patterns• access systems
Columbia University School of Nursing M6920, Fall, 2000
Use of technologies?
•clinical excellence•technological preeminence•profit maximization
•in a fee-for-service system•in a capitated or global budget
system
Columbia University School of Nursing M6920, Fall, 2000
Assessing technology
Is this safe? Efficacious? Effective? Efficient?
• speed of outcome• quality of outcome• cost of outcome
Columbia University School of Nursing M6920, Fall, 2000
Renal dialysis
introduction-late 60's/early 70's use of screening committees ESRD Medicare policy US compared to GB
Columbia University School of Nursing M6920, Fall, 2000
Heart transplant
early 70’s• everybody try one• few centers persist with procedure
mid 80's• introduction of anti-rejection drugs
Columbia University School of Nursing M6920, Fall, 2000
CABG surgery
what are the trade-offs in quality of life?
what about skill/competence• limitations on facilities performing in
NY state
Columbia University School of Nursing M6920, Fall, 2000
BC/BS Technology Assessment Agenda for 1997
Cost Effectiveness Analyses• Cervical Cancer Rescreening Methods• Electron beam computed tomography
for CHD
Columbia University School of Nursing M6920, Fall, 2000
Clinical Effectiveness Analyses• fetal febrnectin• functional sterotactic radiosurgery• genetic testing for colon cancer• neurostimulation for tremor• non-coronary intravascular ultrasound
Columbia University School of Nursing M6920, Fall, 2000
Critical policy problems
who is "disinterested observer" to conduct assessment?• use of consensus panels (NIH/RAND
models)• one discipline? inclusion of "doers"?
• OTA elimination; AHCPR down-sizing defining "experimental"? appeal to the courts
Columbia University School of Nursing M6920, Fall, 2000
Critical research questions
use/role of public opinion professional opinion and practice
• too rapid adoption• delayed adoption
financial incentives to use/not use short and long-term outcomes
Columbia University School of Nursing M6920, Fall, 2000
Hamilton & HO
Objective: understand the relationship between volume and quality
Reason: Is it “practice makes perfect” or selective referral patterns?
Method: regression analysis of 3 years of data
Columbia University School of Nursing M6920, Fall, 2000
Hamilton & Ho, Cont.
Result: negative relationship between volume and length of stay
But: fluctuations in volume had no effect on LOS or mortality
Conclusion: high volume = high quality for reasons other than practice makes perfect
Columbia University School of Nursing M6920, Fall, 2000
Meehan et al.
PRO study to• assess quality of care for Medicare
patients with pneumonia• determine whether process of care
performance is associated with lower mortality
multi-center retrospective cohort study (14,069 patients; 3555 hospitals in US)
Columbia University School of Nursing M6920, Fall, 2000
Mehan et al, cont.
Definition of process of care• time from arrival to antibiotic
administration• blood culture before initial antibiotics• blood culture within 24 hours of hospital
arrival• oxygenation assessment within 24 hours
Columbia University School of Nursing M6920, Fall, 2000
Mehan et al, cont.
Sample Selection• decision on ICD-9-CM codes• exclusion criteria (primarily clinical
confounders such as HIV) Data collection
• training of medical records abstractors
Columbia University School of Nursing M6920, Fall, 2000
Mehan et al, cont.
1/4 of elderly patients do not receive antibiotics until at least 8 hrs post admission; doing so is associated with 15% lower odds of mortality
1/3 of elderly patients do not have a blood culture drawn within 24 hours; doing so associated with 10% lower odds of mortality
Columbia University School of Nursing M6920, Fall, 2000
Mehan et al, cont.
high rate of unconfirmed pneumonia diagnoses when clinical criteria were included
Intriguing query: did presence of DNR orders limit therapy for some patients?
Columbia University School of Nursing M6920, Fall, 2000
Mezey et al
Cross sectional telephone survey Sample of 1016 from 1452 calls
• over 18• English or Spanish speaking• medical or surgical admission• no nursing home pre or post stay
Instrument?
Columbia University School of Nursing M6920, Fall, 2000
Mezey et al
Forced choice answers? Findings
• Racial, language and economic differences
• Level of education most significant
Columbia University School of Nursing M6920, Fall, 2000
Zinn et al
Objective: identify contextual attributes that influence TQM adoption
Data: survey of licensed nursing home administrators, certification files and ARF
Columbia University School of Nursing M6920, Fall, 2000
Zinn et al, Variables
Variable Definition Source
Dependent Variable
TQM Adoption Nsg. Home has adopted TQM survey
Independent Variables
Perceived competition Admin. Perception TQM survey
Herfindal index Nsg home market concentration MMACS
Excess capacity Average # empty beds/county MMACS
Hospital-based substitutes # hospitals providing LTC ARF
Nursing home size # beds in facility MMACS
M’care market penetration Proportion of dischargesMedicare
ARF
HMO membership Proportion of residents in HMO ARF
Proportion Medicare Proportion of NH residents withMedicare coverage
MMACS
Per capita income (log) Average per capita income incounty
ARF
Columbia University School of Nursing M6920, Fall, 2000
Zinn et al, cont.
1: more competitive markets lead to adoption--Partial support
3: facilities in areas with higher M’care discharges more likely to adopt--support
4: facilities in areas with greater HMO penetration are more likely to adopt--significant support
Columbia University School of Nursing M6920, Fall, 2000
Zinn et al, cont
2: Larger facilities are more likely to adopt--no support
5: Facilities with grated proportion of M’care recipients in total census are more likely to adopt--no support
Columbia University School of Nursing M6920, Fall, 2000
Keeler et al
How can a good case mix method be developed?
Combination of birth certificate and hospital discharge data
Retrospective model building effort
Columbia University School of Nursing M6920, Fall, 2000
Keeler et al
Factors ruled out• race and management decisions
Factors had to have• consistent coding practices• unequivocally risk not outcome• prevalence consistent with clinician view• recorded variable associated with outcomes
Columbia University School of Nursing M6920, Fall, 2000
Keeler et al
Merged data better than only one source
Simple model explains 30% of variance among hospitals
Best model explains 37% Is the remainder practitioner
choice???