Haizhen Lin

Revisiting the Relationship between Nurse Staffing and Quality of Care in Nursing Homes: An Instrumental Variables Approach

This paper revisits the relationship between nurse staffing and quality of care in nursing homes using an instrumental variables approach. Most prior studies rely on cross-sectional evidence, which renders causal inference problematic and policy recommendations inappropriate. We exploit legislation changes regarding minimum staffing requirements in eight states between 2000 and 2001 as exogenous shocks to nurse staffing levels. We find that registered nurse staffing has a large and significant impact on quality of care, and that there is no evidence of a significant association between nurse aide staffing and quality of care. A comparison of the IV estimation to the OLS estimation of the first-difference model suggests that ignoring endogeneity would lead to an underestimation of how nurse staffing affects quality of care in nursing homes.

Quality Choice and Market Structure: A Dynamic Analysis of Nursing Home Oligopolies

This article develops a dynamic model of entry and exit to analyze quality choice and oligopoly market structure in the nursing home industry. I find significant heterogeneity in the competitive effects across market structures: Firms of similar quality levels compete more strongly than dissimilar firms. Sunken entry costs are extremely large, and quality adjustment behavior is governed by significant fixed adjustment costs. A proposal to eliminate low‐quality nursing homes is found to cause a large supply‐side shortage, and another proposal to lower entry costs has offered a perverse incentive to provide low quality of care.

Negligence, Causation, and Incentives for Care

We present a new model of negligence and causation and examine the influence of the negligence test, in the presence of intervening causation, on the level of care. In this model, the injurer’s decision to take care reduces the likelihood of an accident only in the event that some nondeterministic intervention occurs. The effects of the negligence test depend on the information available to the court, and the manner in which the test is implemented. The key effect of the negligence test, in the presence of intervening causation, is to induce actors to take into account the distribution of the intervention probability as well as its expected value. In the most plausible scenario – where courts have limited information – the test generally leads to socially excessive care.

Trial Selection Theory: A Unified Model

This paper provides a formal model of the trial selection process that incorporates the Priest-Klein hypothesis and alternative theories of selection. We derive the conditions under which the hypothesis is valid, and examine implications for the relationship between trial outcome uncertainty and litigation. The model suggests a generalization of the hypothesis.

Information Technology and Patient Health: Analyzing Outcomes, Populations, and Mechanisms

We study the effect of hospital adoption of electronic medical records (EMRs) on health outcomes, particularly patient safety indicators (PSIs). We find evidence of a positive impact of EMRs on PSIs via decision support rather than care coordination. Consistent with this mechanism, we find an EMR with decision support is more effective at reducing PSIs for less complicated cases, using several different metrics for complication. These findings indicate the negligible impacts for EMRs found by previous studies focusing on the Medicare population and/or mortality do not apply in all settings.

A Formalization and Extension of the Priest-Klein Hypothesis

This paper provides a formal model of the Priest-Klein trial selection hypothesis, and extends the hypothesis as well. We derive the conditions under which the hypothesis is valid, and examine implications for the relationship between trial outcome uncertainty and litigation.

Hospital Ownership Type and Innovation: The Case of Electronic Medical Records Adoption

Nonprofit and for-profit firms coexist in many industries, with the hospital sector being one of the most predominant examples. This article explores whether nonprofit hospitals are more likely to make expensive investments with uncertain returns and potential public good value. Specifically, we estimate differences in the adoption of electronic medical records (EMRs) by ownership structure. We find that nonprofit hospitals are 11 to 18 percentage points more likely to have installed advanced EMR systems than for-profit hospitals by 2012. Although we find little difference in the likelihood of meeting initial government requirements for the “meaningful use” of EMRs, we find that nonprofits are 12 percentage points more likely to reach more stringent meaningful use standards that began in 2014. That being said, nonprofit adoption rates decrease as for-profit market penetration rates increase, suggesting nonprofits are less likely to adopt an uncertain technology when facing more direct competition from for-profit hospitals.